We recently spoke to Sarah Nooravi, an Analytics professional with a specialism in Marketing who was named one of LinkedIn’s Top Voices in Analytics. Sarah found herself working in Analytics after being attracted to the culture, creativity and the opportunity to be challenged. Having spent the first four years of her career working within the Marketing space, she has seen a real transition in the way that Analytics and Data Science has informed Marketing decisioning. “I started my career in a Marketing agency within the entertainment industry, at the time it was doing things that most of the entertainment industry hadn’t considered doing yet”. At the start of her career she’d meet entertainment giants with advertising budgets of millions of dollars who were, at the time, making mostly gut decisions with how to approach campaigns. “It was common that I’d hear, ‘I think our audience is females over the age of 35 with a particular interest and we should just target them’” she expands. However, agencies quickly recognised the need for something more Data-driven. Entertainment businesses were going too narrow and were misunderstanding their audiences. The next step was to embed into these businesses the insights from a greater variety of sources, including social media, and to introduce more testing. That translated into a better media buying strategy that could be continuously optimised. It was a big step forward in the utilisation of Data within this realm and its clear focus on ROI. Suddenly, the market was changing, “There was a massive spike of agencies popping up and claiming to leverage Data Science and Machine Learning to provide better optimisations for entertainment companies, mobile gaming – you name it. There was a huge momentum shift from using these gut decisions to leveraging agencies that could prove that”. What she saw next seemed only natural, with more agencies offering Data-driven optimisation, companies looked to develop this capability internally. Sarah elaborates; “Now I am seeing these companies starting to take ownership of their own media buying and bringing the Marketing and Data Science in-house”. This shift in-house has been propelled by the major players, companies like Facebook, Google and Nooravi’s own company, Snapchat, working directly with companies to help them optimise their campaigns. This shift has changed the landscape of Marketing Analytics, specifically within the advertising space. Sarah explains, “You no longer need an agency to optimise your, for example, Facebook campaigns, because Facebook will do it for you. They are minimising the number of people behind the campaigns. You give up a little of your company’s Data for a well optimised campaign and you don’t have to hire a media buyer. There is definitely a movement now to becoming more Data-driven. Companies are really leveraging A/B tests and also testing out different creatives”. It is this change in strategy that is seemingly taking the Marketing Analytics challenge to the next level. With opportunities to pinpoint specific audiences, companies are using their Data to understand how to approach their content, take the opportunity to experiment, and to find out what it takes to resonate with their audience. Sarah has seen the potential of this first hand: “We are starting to see a lot of AR and VR. There are meaningful ways to engage with technology to connect with the world. Moving forward, content will have to become more engaging. People’s attention spans are becoming shorter and with each decision someone makes it is changing the direction of content in the future. There has been a massive shift from static images to video advertisement and, more recently, from video into interactive video like playable adverts. People want to engage with adverts in order to understand a company’s message”. It is within this space that she sees a gap for the future of ROI positive advertising: “The biggest issue that I find with the creative and the content is that the value add is missing. The resonance with the brand or company, their values and mission is what is missing. Analytics alone cannot fix that. You need to understand what the company stands for, people want to connect with brands because of what they stand for – whatever it is. Especially in a time like we are dealing with right now, a pandemic, advertising spending has gone down. However, maybe there is a way to properly message to people that would resonate. Not that you want them to buy your stuff but maybe right now is the perfect time to do outreach and to help people understand your brand”. The ability to understand and predict customer behaviour is evolving, but with that, so is the customer. Whereas at the moment, you can build out experiments, you can create models that will be able to, as Sarah explains, “in real-time decide whether a user’s behaviour is indicative of one that is going to churn” and then try and create offers to increase retention. This is the challenge of the current analytics professional – our behaviours in a global pandemic have shifted consumers into a new world. Now working for Snap Inc, she sees the potential of this from a new perspective. Naturally, like most social media channels and communication technologies, they have seen an increase in usage over the last month. “People are wanting to communicate more as we are forced to social distance. However, we are seeing different regions engaging a lot more heavily. For example, it's Ramadan right now, people want to share those moments with one another and at the moment the way that they are having to do that is changing”. So, it will be a question for all those required to predict behaviours to determine how many of these new lines of communication, these new habits, will have evolved. Once people are out of quarantine, are they going to continue to utilise the apps, games, social channels in the same way that they are currently? It certainly is going to be something that many within the marketing analytics space will be trying to forecast. If you’re looking to take your next step in Marketing Analytics, or are looking to build out your team, Harnham may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.
28. May 2020
It’s a challenge finding the right Data & Analytics candidate. Add in the number of companies fighting for that perfect profile and for many it can seem like an uphill battle. But there’s a simple way to cut through the noise; better job descriptions. As a specialist recruitment agency within the Data & Analytics space, we have seen a real variety of job descriptions over the years, from the bright and innovative to the long and technical. And it may surprise you to learn that candidates still ask regularly to see official job descriptions and it is part of their decision-making process. Unfortunately, they are also often a part of the recruitment process that can be rushed or created from out-of-date previous descriptions. There are some real benefits, however, to putting the time and effort required into creating something fresh. If you’ve recruited a role like a Data Scientist before, you know that the problem isn’t usually getting enough candidates through the door, it’s about getting the right ones. A well-crafted job description leads to better quality applicants. It also helps those candidates become more engaged and excited about your business. So, with that in mind, here are our five top tips for businesses looking to help their role stand out from the crowd. CHECK YOUR JOB TITLE You might think that calling your BI Analyst a ‘Data Ninja’ is going to get you the top talent, but it would probably mostly cause confusion. It is important that you align the job title to a clear and market relevant job title. Often internal job titles can be the biggest blocker in aligning your vacancy to the market. Consider changing the job title for external purposes to make it more closely aligned to the market. Here are some common examples: An AVP Analyst within a Marketing Analytics team is more closely aligned to a Senior Marketing Analyst. A Data Scientist job title aligned to a role with no machine Learning or algorithmic development may be better titled a Statistical Analyst. CREATE A COMPELLING JOB RUN-THROUGH Our consultants agreed unanimously that one of the weakest areas of job descriptions tends to be the more detailed description of what the role actually is. Too often job descriptions just list lots of different responsibilities, but these are often very generic or basic. Before starting to write the job brief, ask members of your team that do the role already – what gets them excited? You will likely find that it has to do more with the types of projects i.e. the application of technical elements, that appeals most to candidates. If you can, bring the role to life in a meaningful way. For example, relating it to projects that your team has done is a really enticing method of exciting a candidate about the potential of the role. Create A Tailored Experience Section Uninspiring job descriptions often have long lists of key skills required, often with irrelevant skills included. Keep your requirements to around 5 or 6 key bullet points, asking yourself what the most important requirements are and clearly laying those out. On top of that often companies get too focused on requesting years of experience. We strongly discourage companies from specifying years of experience in a job advert as, within the UK, most European countries and a number of US states this is classified as age discrimination. Instead of including years of experience, carve out what it is that you want your ideal candidate to have done before instead, this will often correlate to their experience level. For example: 5+ years' experience in a Marketing Analytics could easily be transformed to Proven commercial experience in a Marketing Analytics environment with exposure to pre and post campaign analysis, customer analysis, customer segmentation and predictive modelling. DON’T FORGET TO SELL YOURSELVES Another key area where many companies fall down is effectively selling their opportunity and company to the prospective candidates. Whether an active or passive job-seeker, candidates are likely deciding whether this is the right fit for them based on what they are reading. Many job descriptions completely forgo any type of sales pitch above an initial description of what the company does, perhaps because they expect the candidate to know them and want them. These are the areas we’d suggest bringing to life to effectively sell your opportunity: Writing in your brands personality. Consider the right tone of voice to match your company culture and style of working. Introduce yourself. Whether you’re a brand name or not, use this chance to actually tell people about what you really do and what you really stand for. Share what it’s like to work for the company. Include the culture, work environment, targets, challenges and of course reference to perks and benefits on offer too. Consider the candidate. What appeals to a talented Data Scientist will differ from what appeals to an HR professional. Make sure you tailor your overall pitch to the type of candidate you are seeking. WORK ON THE LOOK AND FEEL A little effort on the aesthetic look of your job description an go a long way. On top of a nice overall look, keep the length to a maximum of 1.5 pages. Utilise bullet points and bold formatting to keep the description some-what ‘skimmable’. If you’re looking to hire a Data & Analytics professional, Harnham can help. Get in touch with one of our expert consultants to find out more.
14. May 2020
For our latest LinkedIn Live, we spoke to Alex Kudelka, VP of Revenue at Doodle, Sarah Ogorevc, National Manager, Campus Recruitment at Deloitte Canada, and Nahal Mustafa, Senior Org Development Specialist at Klarna, as well as our own Head of IR, Charlie Waterman. Discussing how tech can support businesses during COVID-19, what this means for hiring and those just joining the workforce, and how you can support and retain your teams during lockdown, this fascinating conversation is well worth a watch for anyone looking to recruit or onboard remotely. Here's what they had to say:
13. May 2020
"I like thinking about how customers experience things and how you’re able to effectively tailor your business to them." We recently had the opportunity to speak with Corin Rogerson, a CRM Specialist and customer champion to discuss all things CRM. Beginning in the digital space she has taken her holistic overview of customer experience with her throughout her career and built CRM programmes for some of the biggest brands on the market. So how has CRM changed during this time and where does she see it going? As we see a general trend towards digital first businesses, online platforms and integrated apps it goes without saying that CRM is having to follow suit. For Corin, potentially one of the biggest changes driven by this is this marketing technology landscape: “I think the main thing I’ve seen is when I first started in CRM there were lots of tools that were offering the ability to communicate with someone through one channel […] and now what I’m quite pleased to see is that some companies are building solutions from the ground up.” This shift from bolted together CRM/ESP’s to streamlined platforms offering the opportunity to build multi-touchpoint journeys now makes it far easier to build synchronised customer experiences. Hand in hand with technology is the ever-increasing presence of data in decision making, and a growing factor in successful CRM: "A few years ago everyone was talking about Big Data, and there are more tools able to process that data now". But within this is the value that Data can bring bought about through "thinking about the Data that is actually important to you and what you can actually use, rather than just pushing everything in." But simply having the Data there isn’t enough to immediately achieve results and one of the biggest issues Corin has faced is around data latency and the impact this has on communication: “In the past if you had Data in 24 hours that was perfectly fine, but now you really need to know virtually in real time what a customer has done to communicate with them effectively […] for instance if a customer’s payment details have expired and there is a lag between them updates and an email going out it can be a really confusing communication.” However, that doesn’t mean that Data hasn’t played a large part in her successes. Customer Data has huge ties to personalisation (another noteworthy trend in the CRM space) and is often the best way to demonstrate the value a customer has to a business as shown through Corin’s biggest successes: “Where I’ve been really successful in a company or working on individual projects is always where the CRM team works really closely with the Data team. Over time you can put in really intelligent campaigns.” So, what is the importance of CRM in today’s climate? Having experienced the power of CRM across businesses at different stages of their journey CRM is ultimately really important for growth. In the case of start-ups “the focus is very much on acquisition and that is partly because of the priorities in early life” but no matter the size of the business “it’s very expensive to acquire a new customer”. As such, Corin suggests bringing in a CRM team and shifting towards a culture of retention over rapid acquisition as soon as possible: “As soon as you bring a CRM team on boards […] you can start looking at your existing customer base and seeing how likely they are to repeat purchase […] the more you keep those customers long term, the better your business will do.” Her biggest pet peeve linked to CRM and growth? Data: “There’s nothing more frustrating than not having the right Data available”. Although the overriding advice is ASAP, it’s with the caveat of an adequate Data infrastructure to allow for the insights to be leveraged. It feels uncomfortable not to acknowledge the elephant in the room and the impact COVID-19 has had on how brands market to customers: “When the pandemic hit a lot of businesses had to take a step back and think, what are our values, what is our proposition and how can we help people in context to the pandemic.” In an ideal world this would then feed into the CRM team yet we’ve all experienced “empty examples of communications from companies who feel they have to say something about it […] and it doesn’t work, and I think it actually does damage to the brand." Corin’s advice on this? "If I was in a CRM team that is what I would be thinking about. Making sure communication is relevant, it’s useful and it’s something that you will then be remembered for when everything is over.” If you’re looking for an opportunity in the world of CRM, or to build your Customer Insight team, we may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to learn more.
06. May 2020
It’s no secret that jobs within the Data & Analytics market are more competitive than ever and with some jobs having hundreds of applicants (if not more), having a CV that stands out is more important than ever. It’s well known that many Hiring Managers spend a short amount of time reviewing a candidate, so you need to consider what they can do to have the best impact. We’ve seen it all over the years, from resumes sorely lacking detail through to those that have almost every accomplishment written over too many pages – so we’ve complied a list of the 10 things that could help you create a resume that makes an impact, complete with top tips from our team of experienced recruiters. 1. Keep it Simple All of our recruiters are unanimous in suggesting to candidates that the perfect CV length is no more than two pages, or one for a graduate or more junior candidate. Sam, our Corporate Accounts manager suggests that candidates keep it simple: “In analytics, it’s all about the detail and less about how fun your CV looks. My best piece of advice would be to keep it to two pages, use the same font without boxes or pictures, and bold titles for the company and role. It sounds pretty simple but it’s really effective and often what our clients seem to be drawn to the most”. 2. Consider the audience & avoid jargon Before your CV gets to the Hiring Manager, it may be screened by an HR or recruitment professional so it’s crucial to ensure that your CV is understandable enough that every person reviewing it could gauge your fit. Whilst showing your technical ability is important, ensure that you save yourself from anything excessively technical meaning only the Hiring Manager could understand what you have been doing. 3. Showcase your technical skills There is, of course, a need to showcase your technical skills. However, you should avoid a long list of technologies, instead clarify your years of experience and competence with each of the tools. Within the Data & Analytics market specifically, clarifying the tools that you used to analyse or model is very important and writing those within your work experience can be very helpful. Wesley, who heads up our French team, explained where candidates can often go wrong: “Candidates often write technical languages on their CV in long lists and forget to make them come to life. My clients are looking for them to give examples of how and when they have used the listed tools and languages” 4. Consider the impact of your work Just writing words such as ‘leadership’ or ‘collaboration’ can often easily be over-looked. It’s important that you are able to showcase the impact that you work has beyond the traditionally technical. Think about how you can showcase the projects that you have lead or contributed to and what impact it had on the business. Often people forget the CV isn’t about listing your duties, it’s about listening your accomplishments. Ewan, our Nordics Senior Manager brings this to life: “I would always tell someone that whenever you are stating something you did in a job you always follow up with the result of that. For example, ‘I implemented an Acquisition Credit Risk Strategy from start to finish’ – but then adding, ‘which meant that we saw an uplift of 15% of credit card use’”. Joe, New York Senior Manager, concurs: “Actionable insights are important, results driven candidates are what our clients are looking for. So instead of ‘Implemented A/B Testing’, I’d get my candidates to make that more commercial, such as ‘Implemented A/B test that result in 80% increase in conversion’”. 5. Use your Personal Summary A personal summary is effective when it comes to technical positions, as some people can often overlook them. Use this to summarise your experience and progression as well as indicate the type of role and opportunity you are looking for. If this is highly tailored to the role you are applying for, it can have an extremely positive impact. For example: ‘Highly accomplished Data Scientist, with proven experience in both retail and banking environments. Prior experience managing a team of five, and proven ability in both a strategic and hands on capabilities. Proven skills in Machine Learning and Statistical Modelling with advanced knowledge of Python, R and Hadoop. Seeking Data Science Manager role in a fast-paced organisation with data-centric thinking at it’s heart’. 6. Consider what work and non-work experience is relevant If you’ve been working in the commercial technical sphere for more than five years, it’s likely that your part time work experience during university or the non-technical roles that you took before you moved into your space are no longer as relevant. Ensure you are using your space to offer the Hiring Manager recent, relevant and commercially focused information. However, do not leave gaps just because you took a role that didn’t relate to your chosen field, you don’t need to describe what you did but have the job title, company and dates to ensure you are highlighting a clear history of your experience. It’s important to note that you are more than just your work experience as well, Principal Consultant Conor advises candidates to talk about more than just their work accomplishments: “Listing non work achievements can help make the CV stand out. If someone has a broad range of achievements and proven drive outside of work, they will probably be good at their job too. Plus, it’s a differentiating point. My clients have found interesting talking points with people who have excelled in sports, instruments, languages and more specifically for the Analytics community – things like maths and Rubik’s cube competitions”. 7. Don’t forget your education For most technical roles, education is an important factor. Ensure that you include your degree and university/college clearly as well as the technical exposure you had within this. If you did not undertake a traditionally technical subject, make sure you highlight further courses and qualifications that you have completed near this section to highlight to the Hiring Manager that you have the relevant level of technical competence for the role. 8. Don’t include exaggerated statements It goes without saying that if you are going to detail your experience with a certain technical tool or software that you could be asked to evidence it. Saying your proficient in R when you’ve done a few courses on it won’t go over well, especially if there are technical tests involved in the interview process. At the same time, don’t undervalue your expertise in certain areas either, your strengths are what the Hiring Managers is looking for. 9. Don’t get too creative Unless you’re in a creative role it’s unlikely that the Hiring Manager will be looking for something unique when it comes to the CV. In fact, very few people can pull of an overly flashy CV, most of them being those that work specifically in design. When in doubt, stick to standard templates and muted tones. 10. Tailor, Tailor, Tailor! Time is of the essence and when it comes to reviewing CVs and you don’t have long to make an impact. Make sure to customise your resume using keywords and phrases that match the job description (if they match your own, of course). For example, if the role is looking for a Business Intelligence Analyst with proven skills in Tableau you would not just claim, “experience in Data Visualisation”, you’d list the software name, “experience in Tableau based Data Visualisation”. Although every job description is different, all it takes is a few small tweaks to ensure your maximising your skillset. If you're looking for your next Data & Analytics role or are seeking the best candidates on the market, we may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.
30. April 2020
We recently spoke to Vin Vashishta, a consulting Data Scientist and Strategist who was named one of LinkedIn’s Top Voices in Data Science. Having started off in the tech world 25 years ago and progressing from web design and hardware installation to Business Intelligence Analytics, Vin found for many years that enterprises were reluctant to adopt AI technologies and embrace the value of Data. In fact, it wasn’t until the beginning of the decade just passed that companies started to think about their Data more strategically and the world of Data Science was born, albeit hesitantly: “When I first started, it was a lot of experimentation, everyone wanted a proof of concept,” he says. “A lot of work was creating models that could go from whiteboard to production and productise and show their value.” However, it wasn’t until halfway through the decade that he began to see businesses who had adopted Machine Learning move away from experimentation into incorporating it more deeply into their companies, relying more on analytical and optimisation models to make strategic business decisions. “After that, in about 2017/2018 the maturity changed. It went from being a one off implementation to it being a comprehensive tool within an organisation where we have full lifecycles of model implementation and full models that were full views of the system. The key component of development was allowing users to access a small part of the system to do their job better without having to understand the whole thing. And that’s where we are now. We have this applied Deep Learning and we are seeing, especially this year, attempts to optimise that, make things go faster and make them more repeatable.” But, as we all know, with great power comes great responsibility: “There’s this whole depth we are getting into, the expectations are so much higher, people don’t just expect it to work they expect it to work the way they want it to and in a way they can adopt.” So, with so much expected and required of Data Scientists in 2020, building the right team is more important than ever. However, many businesses, Vin believes, are yet to get their hiring processes right: “A lot of the measures that we use to sort of evaluate employees are fictional – when you say years of experience, it has no correlation to employee outcomes or the quality of employee you get long term. It’s the same thing as college degree, there’s no correlation.” So when Vin is trying to build a highly specialised team, what does he do? “We have to teach specialisation, we can’t expect it. We can’t bring someone in and call them a Data Scientist and hope that they train up. You end up with teams that are exactly the same because they have hired the same people, people who reinforce the bias of what they do, and that is where true leadership needs to come in.” A specialised team made up of individuals who bring their own ideas to the table is more important than ever, particularly as businesses demand more from their Data teams. Gone are the days of one-size-fits-all models. Businesses now want something tailored to them: “Custom models are huge. The “import from…” Machine Learning development from three years ago adds value when it comes to wrangling and doing the Analysis, but when it comes to creating models companies are now expecting it to become a competitive advantage. Companies no longer want the same model that everyone else has, now it has to be differentiating.” These smart, customised models, he adds, will help businesses through the current pandemic. “The best models right now are adapting rather than reacting.” However, he’s sceptical about the Data Science community becoming too preachy: “When it comes to COVID-19 one message I want to send to the Machine Learning and Deep Learning community is ‘shut up’. We don’t have the Data! We have so many Data Scientists talking about something that’s very important to get right. If you get it wrong the consequences and the credibility we will lose as a field is enormous.” Indeed, discussions about the lack of quality Data on COVID-19 are widespread at the moment and raise concerns for Vin: “What the last two and a half months has revealed is the danger of bad Data, the danger of assumptions that are hidden in Data that hasn’t been looked over well or wasn’t gathered well and was fed into these models that now aren’t robust. Of course, no model can account for something this drastic, but they should still be performing far better than they are right now.” Despite these concerns, Vin believes any change in the world brings about opportunities for those in the Data and technology space. “What I’ve been trying to do ever since I joined the technology space is figure it out. It’s constantly evolving and it’s constantly changing. That’s really what has driven my journey. I’m always trying to figure out ‘what’s next’ over the next five years, ten years whatever it may be.” If you’re looking for your next Data Science, Machine Learning or Deep Learning role, or want to build out your own highly-specialised team, we may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.
23. April 2020
Wir hatten kürzlich die Gelegenheit mit Rachel Stuve, einer von LinkedIns Top-Stimmen in Data Science & Analytics und Geschäftsführerin der Data Teams, zu sprechen. Als eine Expertin in ihrem Gebiet verfügt Stuve über ein breites Erfahrungsspektrum. Nachdem sie die Universität im automobil-lastigen Michigan absolviert hatte, war ihr erster Job bei Chrysler die Autoindustrie zu analysieren. Kurz nachdem sie in die lokale Verwaltung gewechselt war, digitalisierter und integrierte sie deren Strafverfolgungsprozesse, bevor sie an einer landesweiten Initiative zum Datenaustausch arbeitete. Zuletzt war das Gesundheitswesen Stuves Fokus. Während viele diese Branche als hochspezialisierte, unzugängliche Branche ansehen, ist Stuve einer anderen Meinung. "Es sind alles übertragbare Fähigkeiten. Möglicherweise betrachten Sie unterschiedliche Datensätze bei einem Gesundheitsdienstleister, aber im Wesentlichen, erfolgt die Analyse nach denselben Prinzipen. Dennoch stellt Stuve klar, dass man trotzdem einige Hürden, vor allem terminologische, überwinden muss. "Zugegeben, der Jargon ist etwas gewöhnungsbedürftig und es gibt davon viel." Jedoch die Hauptunterschiede sind weniger wissenschaftlicher Art und mehr in Hinblick auf die Infrastruktur. Anders als viele datengesteuerten Industrien liefern Krankenversicherer nicht direkt an den Verbraucher. Tatsächlich ist deren eigentliche Beziehung mit den Gesundheitsdienstleistern. "Es ist nicht dasselbe, wie eine Hypothek aufzunehmen. Sie werden sich nicht direkt an ihren Versicherer, damit dieser sich um Sie kümmert. Ihr direkter Service ist der Gesundheitsdienstleister, das Krankenhaus und es ist lediglich die Aufgabe des Versicherers die Zahlungen zu decken. Ein Teil der Herausforderung ist es, herauszufinden, welcher Anbieter das beste Preis-Leistungs-Verhältnis aufweist und welcher eine hochwertige Versorgung anbietet." Dies bedeutet, dass es wichtig ist, ein Team aus Datenwissenschaftlern und Epidemiologen zusammen zusetzten. Epidemiologien können besser identifizieren, welche Behandlungen erzielen den größten Erfolg, bei möglichst geringen Kosten. Wie kann man nun solch ein Team, mit unterschiedlichen Hintergründen und Herangehensweisen dazu bringen, harmonisch miteinander zu arbeiten? "Ob von Anfang an die richtigen Ziele vereinbart wurden, hat großen Einfluss auf den Erfolg eines Projekts. Wenn sich alle Teammitglieder einigen können, wie genau Erfolg aussieht, sei es 10, 20% Gewinnsteigerung, oder ein anderes Ziel, dann weiß jeder worauf man hinarbeitet. Natürlich gibt es ab und an Diskussionen über statistische Gespräche, aber schlussendlich ziehen alle an einem Strang." Stuve betont auch, wie wichtig es ist, die richtigen Personen in der richtigen Projektphase einzubeziehen. All zu oft werden die Endnutzer nicht in die frühen Datenprojektphasen miteinbezogen, was zu großen Wissenslücken führt. Stuve stellt fest: "Mit ziemlicher Sicherheit werden Sachen übersehen, wenn diejenigen, die wirklich wissen, was sie von einem Projekt benötige, nicht von Anfang an miteinbezogen werden." Neben ihrer Arbeit im Gesundheitswesen, investiert Stuve ihre Arbeit bei Golden Seeds auch in von Frauen geführte Start-ups. Eine Angelegenheit, die ihr besonders am Herzen liegt. "Ich liebe Golden Seeds. Es existieren zahlreiche Studien, die belegen, dass Frauen geführte Unternehmen höhere Rendite erzielen, dennoch erhalten diese Unternehmen, im Vergleich zu von Männern geführte Unternehmen, nur einen Bruchteil von Investitionen." Sie verweist auf einen kürzlich in der Harvard Business Review veröffentlichten Artikel, weshalb dies sein könnte. Laut des Artikels besteht, bei dem Investmentprozess, eine gewisse Geschlechtervoreingenommenheit. Männlichen Unternehmer werden nach dem Potenzial des Unternehmens gefragt, weibliche Unternehmerinnen hingehen eher nur rein risikomindernde Fragen. "Leute investieren in Optimismus. Wenn Unternehmerinnen also nicht die gleiche Möglichkeit gegeben werden den 'Traum' zu verkaufen, dann ist die Wahrscheinlichkeit eine Investition zu bekommen um einiges geringer." Auch glaubt Stuve, dass eine Wahrnehmung besteht, dass von Frauen geführte Unternehmen weniger innovative sind: „Ich möchte das Verständnis ändern, dass diese Unternehmen als „mädchenhaft“ bezeichnet werden und sich ausschließlich auf Kleidung, Lebensmittel oder den Einzelhandel konzentrieren. Das ist, meiner Erfahrung nach, nicht der Fall. Frauen stehen an der Spitze aller Branchen, von Biotechnologie über Energie bis hin zu einer Reihe von Fachgebieten.“ Also, worauf achtet sie beim Investieren? "Natürlich suche ich nach einer innovativen Idee, welche ein Geschäftsbedürfnis erfüllt, aber zugleich investiere ich auch in die Person. Sind sie realistisch? Sind sie starke Anführer? Sind sie sich ihren eigenen Schwächen bewusst und haben sie ein Team um sich herum aufgebaut, welches diese Schwächen ausbalancieren kann?" "Leider besteht eine Doppelmoral, wenn es um die Wahrnehmung männlicher und weiblicher Führungskräfte geht. Dies bedeutet, dass die Art und Weise, wie sie sich selbst tragen, einen großen Unterschied macht, besonders wenn sie nach weiteren, zukünftigen Investitionen suchen." Stuve ist sich der Schwierigkeiten, mit denen Frauen in Männerdominierenden Brachen konfrontiert werden, durchaus bewusst. Sie selbst war in vielen Teams die einzige Frau, insbesondere als sie in das Management aufstieg. Glücklicherweise sieht sie ein Licht am Ende des Tunnels: "Unternehmen fangen an zu erkennen, wie wichtig es ist, die Vielfalt ihrer Teams zu erweitern und das Unternehmensgespräch passen sich dies auch an." "Darüber hinaus besteht ein großartiges Data-Netzwerk von Frauen. Das Verknüpfen hat einen Schneeballeffekt. Sie verknüpfen sich mit einer Person, welche ihnen eine andere Person vorstellt, die ihnen wieder eine andere Person vorstellt und so weiter, bis ihnen die Reichweite dieser erstaunlichen Gemeinschaft außergewöhnlicher Frauen bewusst wird." Wenn Sie mehr von Rachel Stuve hören möchten, können Sie ihr auf LinkedIn folgen, um regelmäßig mit Updates und Ideen versorgt zu werden. Für weitere Informationen zum aktuellen Stand der Vielfalt in Data & Analytics finden Sie hier in unserem Bericht zu diesem Thema. Wenn Sie Ihr Team ausbauchen möchten oder nach einer neuen Herausforderung suchen, können Sie sich an einen unserer Fachberater wenden oder sich hier über unsere neuesten Möglichkeiten informieren.
21. April 2020
We recently spoke Nisha Iyer, Head of Data Science, and Nupur Neti, a Data Scientist from Data Society. Founded in 2014, Data Society consult and offer tailored Data Science training for businesses and organisations across the US. With an adaptable back-end model, they create training programs that are not only tailored when it comes to content, but also incorporate a company’s own Data to create real-life situations to work with. However, recently they’ve been looking into another area: toilet paper. Following mass, ill-informed, stock-piling as countries began to go into lockdown, toilet paper became one of a number of items that were suddenly unavailable. And, with a global pandemic declared, Data Society were one of a number of Data Science organisations who were looking to help anyway they could. “When this Pandemic hit, we began thinking how could we help?” says Iyer. “There’s a lot of ways Data Scientists could get involved with this but our first thought was about how people were freaking out about toilet paper. That was the base of how we started, as kind of a joke. But then we realised we already had an app in place that could help.” The app in question began life as a project for the World Central Kitchen (WCK), a non-profit who help support communities after natural disasters occur. With the need to go out and get nutritionally viable supplies upon arriving at a new location, WCK teams needed to know which local grocery stores had the most stock available. “We were working with World Central Kitchen as a side project. What we built was an app that supposed to help locate resources during disasters. So we already had the base done.” The app in question allows the user to select their location and the products they are after. It then provides information on where you can get each item, and what their nutritional values are, with the aim of improving turnaround time for volunteers. One of the original Data Scientists, Nupur Neti, explained how they built the platform: “We used a combination of R and Python to build the back-end processing and R Shiny to build the web application. We also included Google APIs that took your location and could find the closest store to you. Then, once you have the product and the sizes, we had an internal ranking algorithm which could rank the products selected based on optimisation, originally were based on nutritional value.” The team figured that the same technology could help in the current situation, ranking based on stock levels rather than nutritional value. With an updated app, Iyer notes “People won’t have to go miles and stand in lines where they are not socially distancing. They’ll know to visit a local grocery store that does have what they need in stock, that they’ve probably not even thought of before.” However, creating an updated version presented its own challenges. Whereas the WCK app utilised static Data, this version has to rely on real-time Data. Unfortunately this isn’t as easy to come by, as Iyer knows too well: “When we were building this for the nutrition app we reached out to groceries stores and got some responses for static Data. Now, we know there is real-time Data on stock levels because they’re scanning products in and out. Where is that inventory though? We don’t know.” After putting an article out asking for help finding live Data, crowdsourcing app OurStreets got in touch. They, like Data Society, were looking to help people find groceries in short supply. But, with a robust front and back-end in place, the app already live, and submissions flying in across the States, they were looking for a Data Science team who could make something of their findings. “We have the opportunity,” says Iyer “to take the conceptual ideas behind our app and work with OurStreets robust framework to create a tool that could be used nationwide.” Before visiting a store, app users select what they are looking for. This allows them to check off what the store has against their expectations, as well as uploading a picture of what is available. They can also report on whether the store is effectively practising social distancing. Neti explains, that this Data holds lots of possibilities for their Data Science team: “Once we take their Data, our system will clean any submitted text using NLP and utilise image recognition on submitted pictures using Deep Learning. This quality Data, paired with the Social Distancing information, will allow us to gain better insights into how and what people are shopping for. We’ll then be able to look at trends, see what people are shopping for and where. Ultimately, it will also allow us to make recommendations as to where people should then go if they are looking for a product.” In addition to crowdsourced information, Data Society are still keen to get their hands on any real-time Data that supermarkets have to offer. If you know where they could get their hands on it, you can get in touch with their team. Outside of their current projects, Iyer remains optimistic for the world when it emerges from the current situation: “Things will return to normal. As dark a time as this is, I think it’s going to exemplify why people need to use Artificial Intelligence and Data Science more. If this type of app is publicised during the Coronavirus, maybe more people will understand the power of what Data and Data Science can do and more companies that are slow adaptors will see this and see how it could be helpful to their industry.” If you want to make the world a better place using Data, we may have a role for you, including a number of remote opportunities. Or, if you’re looking to expand and build out your team with the best minds in Data, get in touch with one of expert consultants who will be able to advise on the best remote and long-term processes.
14. April 2020
Covid-19 has presented a challenge for recruiting teams and businesses across the globe. Many businesses have adjusted to remote working in order to help stop the spread and eliminate the need for their employees to travel to the office. As businesses continue to hire, they are using technology to move from a traditional face to face process to video interviews. The good news for companies who are on the hunt for top talent, however, is that now is a prime time to continue speaking and networking with Data & Analytics professionals who could be a great addition to their business. Here’s why: AN EXCESS OF FREE TIME Now that people are working from home, they’re saving time on commuting, and aren’t working in close proximity with their co-workers or boss so they can make time to speak. Any previous struggles with arranging times to speak because of clashing schedules are now significantly reduced and there is now plenty of time to book in a call. Isolation is a prime time to hold a conversation with potential future employees as it’s highly doubtful anything is going to pop up last minute and interrupt your meeting. Plus people are more keen than ever to keep connected to others and engage with conversation. It’s the perfect opportunity to softly sell your company and what is on offer, longer term company visions, discuss trends in the market, plans on growing and where the best Data & Analytics talent around can fit into this. WE’RE ALL TECH READY With the world now set up for remote working, this could be a great time to book in virtual coffee meetings over the likes of Zoom, Google Hangout or Skype. Adjusting from face to face meetings to virtual ones, means there is no need to cancel meetings and if anything means networking with talent is easier. There are plenty of opportunities to ‘meet’ with talent and build relationships in ways that may have been harder to arrange when trying to find a physical time and place. This also means that onboard remotely is a very achievable reality. Virtual meetings with new starters offer an easy way to stay connected and build a relationship before they join the business. For example, a candidate who accepted a job offer in February but now may not start until August could be feeling uncertain as to whether there is still a job on offer. By arranging virtual meetings with people who are still set you join the company you’ll be able to stay in contact,. keep them engaged with your brand, and actually have longer to build a pre-onboarding relationship with them than you would’ve done. CANDIDATES ARE READY TO GO The best talent doesn’t wait around for long and, if projects have been postponed, they’ll be keen to keep developing their skillset Specialist and highly skilled candidates who may not have been looking for new opportunities are now actively searching and more than willing to network with hiring managers. Even if you’re not imminently hiring, now is a good time to begin initiating longer term conversations with professionals and creating a pool of talented candidates who are engaged with the business. Then, by the time you are ready, there will be a talent pool to begin interviewing with rather than starting from scratch. Naturally, some candidates may no longer be on the market, but if they’ve been left with a positive impression, there’s no harm staying in touch until the right time does come along. If you’re looking to connect with top Data & Analytics talent or businesses, we can help. Get in touch to hear about our network of thousands of top Data professionals, or take a look at our latest opportunities here.
09. April 2020
If you’re preparing for an interview, video or otherwise, it’s important to think beyond Googling ‘common interview questions’ and scanning the company’s website. It’s important to make a great first impression and by preparing properly, you’re in a better position to achieve this. Plus, you’ll feel more confident and will be able to give more convincing answers that will help prove why you’re the perfect fit for the role. With that in mind, here are our recommendations for how to best prepare for an interview: Find out what type of interview it is Even if a company isn’t working entirely remotely, it’s likely you’ll face a variety of interviews throughout a their application process. Most processes last between two and three stages of interviews, any many vary in how these are conducted. They could be: Face to Face – Expect these to last between 45 minutes and 2 hours. The questions will be likely be strengths- or competency-based. Phone – This is often used early in the process, we’d expect these to last approximately 30 minutes and are designed to get a feel for your skillset and experience. Video – These are becoming increasingly popular with employers, and can be live or pre-recorded. They tend to last around 30 minutes. Assessment Centres – You’ll attend these with other candidates and take part in a variety of tasks presentations, team exercises and psychometric tests lasting a full day. Get to know the company Don’t just look at their About Us page. Read about them, their clients and their products or services. This will help you learn about what they do but also learn how they see themselves as business and what they feel makes them different from their competitors. This will help your interviewer understand you ‘get’ them and understand their business. Research the team As well as getting to know the company, we’d recommend taking a look at your interviewer’s LinkedIn profile and seeing what they’ve posted and where they’ve come from. Also, take a look at the “Meet the team” pages on the website to gain an insight into who you may be meeting throughout your process. Glassdoor is a good place to go for company reviews but take them as a guide not fact as they’re anonymous reviews by current or former employees. Prepare your own questions It’s likely your interviewer will ask what questions you have for them. This is a great opportunity for you to get the information you need to figure out if this is a job you really want and can see yourself doing. Think about what you really want to know about the position and the company. Things to think about could be: What are the biggest challenges in this position? What would be the expectations of me 3/6/12 months in? Could you describe what a typical day is like in this position? Not only does this help you build a bigger picture of what this job would look like, your questions show a deeper engagement in the role and company, much more so than asking basic questions such as “What’s the salary? What is the holiday allowance? What are the working hours?”. It’s perfectly normal to write down your questions and take them into your interview to avoid forgetting any questions you wanted to know the answers to, so don’t feel as though you can’t do this. Re-read the job description Spend time highlighting the responsibilities in the job description and thinking how your experience equips you to meet these. Try to prepare concrete examples from your past that back up why you’d be great for the role. How have you dealt with challenges or what successes have you had that you can link to how you’d be successful in this role? Try to come up with at least 5 solid examples or stories to talk through in the interview. Write down questions you’re likely to be asked There are some questions you can almost guarantee on being asked such as “tell me about yourself” or “what is your biggest weakness”. It’s also likely you’ll be asked questions around your interest in the role and the company and why you applied. Be prepared to talk about numbers, in particular any significant impact that your previous projects have made on a business. For each question you think of jot down a few notes or bullet points to build upon instead of writing out an entire answer and trying to remember it word for word. Practice saying your answers Practising your answers out loud and looking in the mirror will help you clarify your answers and make you more comfortable during the interview. Try doing a mock interview with a friend or family member to help polish your delivery and boost your confidence in what you’re saying. Dress accordingly Figure out what to wear to the interview by asking what the office dress code is before the interview. If the business has a business casual or business dress code, it’s appropriate to wear a suit for males and females to dress in smart business attire. Make sure your outfit and shoes are clean and your bag/briefcase is emptied of any rubbish and packed with interview essentials: pens, a notepad, a copy of your CV, list of questions, mints, business card. These may seem obvious, but employers do take note and still make judgements based on how you present yourself. If you’re looking to take the next step in your career, or if you’re looking for help with your next hiring process, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.
07. April 2020
If Fraudsters are anything, they are opportunists. Once the first new stories about COVID-19 started running, it wasn’t long until they were joined by tales of fraudsters selling face masks and hand sanitiser, asking panicked customers to transfer money and then disappearing without a trace. And it’s not the first time we’ve seen this. Fraudsters are notoriously wise to periods of heightened sensitivity and uncertainty, often preying on the vulnerable. The 2008 financial crisis saw an increase in email-based phishing scams and a decade’s worth of technological advancements means that Fraud remains a many-headed beast. Add into the mix a change in working styles and environments, and many businesses are more exposed to potential security breaches than they have been in years. Now, more than ever, companies need to make sure their Data is well protected and secure. THE FIRST LINE OF DEFENCE If you’re part of, or leading, a Fraud Prevention team, there are a number of ways you can support your business and keep on top of the situation. Here are just a few: Increase and update your investigation capacity. This team are the front line of your business’ Fraud defence team, interacting with customers daily and spotting new scams. During an uncertain period, retention and team stability is key. These are the people that understand the day-to-day Fraud challenges you face and will be essential in fighting any future challenges. Sharing Fraud Prevention knowledge is key. Throughout this crisis, trends will be evolving quickly and working collaboratively across teams, and even other businesses, is the best way to combat this. We consistently hear from Fraud Managers that the key to beating Fraud is to share information and knowledge. Despite this, there is always a hesitation amongst companies to admit that they have been a victim to an attack. Perhaps now is the time to change this. Invest in Machine Learning and real time updates for your Fraud defences. Fraud technology has moved on from script writing in SQL and rule changes. Businesses need a real time reactive response and now is an important time to be embracing new technologies. There are a number AI-driven off the shelf packages available or, for a more bespoke solution, a Fraud Data Scientist can create something internally. Educate your team. It may seem simple, but the Fraud team can play a crucial role in minimising any potential risk from human-error. Educating employees on the risks they may face when working remotely, or what scams they need to look out for, is one of the most effective ways of fighting Fraud. PREPARING YOUR BUSINESS Success in the fight against Fraud isn’t purely down to the group of individuals that make up the Fraud team. As a business, now is the time to be making decisions that can help you stay ahead of the Fraudsters. Here are some considerations: Consider investing in tech as an your immediate response. Not just to bolster your Fraud defences (although there are plenty of vendors offering AI-based solutions), but also technology for your employees to keep work as normal as possible such a sharing platforms, DevOps technology and video calling networks. One of the best ways to block some of the vulnerability loopholes fraudsters are trying to exploit is to keep working habits as close to normal as possible as you move to a remote solution. Be transparent with your customers. Consumers are being incredibly savvy and noting how businesses respond to the pandemic in a way that could have a big impact when normality returns. But they’re also being more empathetic and are willing to understand difficulties. For example, shopping delivery service Ocado were open and transparent when their system could not initially deal with demand. Having communicated the difficulties, worked through their issues and gone the extra mile to let customers know how they can be supported in this time, the received minimal backlash. There is an understanding that we’re all in this together. Finally, if you have the budget, continue to staff up - particularly in competitive fields such as Data Science. A lot of top Data professionals are currently at home and much more accessible than they have been in a long time. With a number of ways to remotely interview and onboard both permanent and contract staff, if you are able to get begin conversations with them now, you’ll have an edge in what will be a very competitive market come later in the year. If you’re looking to take your next step in the world of Fraud, we may have a role for you, including a number of remote opportunities. Or, if you’re looking to expand and build out your Fraud team, get in touch with one of expert consultants who will be able to advise on the best remote and long-term processes.
01. April 2020
Jacob Glanville aus der neuen Netflix Serie „Pandemic“, berichtet über die wegweisenden Fortschritte, welche er und sein Team bei Distributed Bio in der Welt der biotechnologisch hergestellten Medizin erzielt haben. Diese Woche haben wir uns mit Distributed Bio’s CEO Jacob Glanville, Feldführer der fortgeschrittenen rechnerischen Immuntechnik der Biomedizin, zusammengesetzt. Die neue Netflix Serie "Pandemic“ gewährt einen Einblick in die Teams, welche derzeit alles versuchen, um einen globalen Ausbruch der Krankheit zu verhindern, und Glanville, ein sehr renommierter Experte mit einer unglaublichen Erfolgsbilanz. Bevor er Distributed Bio gegründet hat, erlangte Jacob Glanville einen PhD der Universität Stanford und arbeitete vier Jahre als leitender Wissenschaftler bei Pfizer. Das Team, geführt von Sarah Ives, Geschäftsführerin Influenza Centivax bei Distributed Bio, entwickelt momentan eine neue universelle Art wegweisender Computertechnologie. Derzeit verwenden wir rechnerisches Ankoppeln mit hohem Durchsatz, um charakterisieren zu können, wie viele einzigartige Epitope auf der Oberfläche eines viralen Hüllproteins oder eines Pathogenproteins existieren können. Danach verwenden wir diverse Berechnungsmethoden, um die unterschiedlichen Elemente der jeweiligen Arten von viralen Kostenproteinen aus verschieden entwickelten Versionen desselben Pathogens identifizieren zu können. Dieses ist das Kernstück unserer Impfstofftechnologie. Wir verabreichen eine Reihe von sehr unterschiedlichen Varianten zeitgleich mit einer niedrigen Dosis, sodass die gemeinsam genutzten Stellen eine ausreichend hohe Dosis aufweisen, um darauf reagieren zu können." Diese Technik ermöglicht es Distributed Bio, Impfstoffe für fast jedes Virus schnell in einer sicheren Umgebung herzustellen. Zum Beispiel, aufgrund des jüngsten Ausbruchs des SARS-Coronavirus, arbeitetet Glanville mit dem US-Militär zusammen. Ein Programm der Weltgesundheitsorganisation ermöglicht die Herstellung von Pseudo-Virion-Versionen der Krankheit, welche untersucht werden können, ohne jegliches Risiko darzustellen: "Sie nehmen die Windpocken und lassen die Außenseite der Windpocken überlaufen, das Kostenprotein der schwerwiegenderen Krankheiten, wie das Coronavirus. Somit verhält es sich nun wie das Coronavirus und sieht äußerlich auch so aus. Es ist wie die knusprige äußere M&M Schale, ähnlich wie das Coronavirus, jedoch innerliche ist es eher wie weichen, klebrigen Schokolade, wie die Windpocken. Es ist nicht sonderlich gefährlich dadurch. Wir bauen eine Beziehung mit dem Militär auf, durch welche wir unsere Antikörperentdeckungsbibliothek in Verbindung mit Pseudovirionpartikeln verwenden können. So können wir schnell Antikörper entdecken, zum Beispiel gegen SARS, ohne SARS Risiko in unser Labor zu bringen.“ Jedoch beschränkt sich ihre Arbeit nicht nur auf die Bekämpfung von Viruserkrankungen. Eines der führenden Projekte von Distributed Bio konzentriert sich auf die Erschaffung eines universellen Gegengifts gegen Schlangenbisse. Die Notwendigkeit eines erschwinglichen Gegengifts mit einfachem Zugang ist hoch, da 80.000 bis 130.000 Menschen jedes Jahr durch Schlangenbisse, die meisten davon in Dritte-Welt-Ländern, getötet werden. "Es existieren ungefähr 550 Schlangenarten und jede hat 20 bis 70 Proteine. Es hört sich nach einer hohen Anzahl von Proteinen an, welche analysiert werden müssen. Aber wenn ich diese analysiere, werden 10 verschiedene, homologe Gruppen, die alle Schlangenarten teilen, deutlich." Nachdem herausgefunden wurde, dass ein universeller Ansatz sowohl möglich als auch realisierbar war, wie wurden die benötigten Antikörper entwickelt? "Unser Team, geleitet von Tim Friede, Geschäftsführer für Herpetologie bei Distributed Bio, Sawsan Youssef, Wissenschaftlicher Geschäftsführer und Raymond Newland, leitender Wissenschaftler, hat einen Mann gefunden, der Schlangen so sehr liebt, das er sich 17 Jahre lang Schlangengift aus aller Welt injiziert hat und dessen Blut haben wir testet. Wir haben Labor- und Berechnungsmethoden verwendet, um eine Reihe von Antikörpern zu identifizieren, welche eine gemeinsame Bestimmungsfaktoren aufweist.“ Bei einem Team, dessen Rollenspektrum sich von Dateningenieuren und Datenwissenschaftlern bis hin zu Bioinformatikspezialisten streckt, ist die Fähigkeit einer Zusammenarbeit besonders wichtig. Wie schafft Glanville solch ein kollaboratives Umfeld? "Ich versuche die Mitarbeiter so gut wie möglich weiterzubilden. Meiner Meinung nach werden Annahmefehler verringert, indem man die Mitarbeiter stetig weiterbildet. Ich denke der häufigste Grund, weshalb Missverständnisse und Fehler aufkommen, ist, da Mitarbeiter nicht verstehen, was ein anderer Mitarbeiter benötigt und was ihnen von der vorherigen Person weitergegeben wurde. Wenn Mitarbeiter im Stande sind, das Fachwissen ihrer Kollegen mit in die Arbeit einzubeziehen, wird dieses Risiko reduziert." Glanville ist in Guatemala aufgewachsen und ist sich dadurch der Notwendigkeit leicht verfügbarer und wirksamer Impfstoffe sehr bewusst. Besonders die westliche Welt wird immer vorsichtiger, was Infektionen angeht, aufgrund von der hohen Menge an Fehlinformationen, die sich derzeit im Umlauf befinden. Er versteht jedoch, dass dieses oft mit Vertrauen zusammenhängt. "Es ist schwierig, der Weltbevölkerung eine epidemiologische Empfehlung zu übermitteln. Oftmals werden keine Impfungen sind besser empfunden. Ich hoffe, dass ein effektiver Impfstoff dieses Fehldenken verschwinden lässt. Leider ist es derzeit noch das Problem einer Grippeimpfung, dass diese nur die Hälfte der Zeit funktioniert. Und das führt dazu, das Menschen anfangen, sich zu beschweren. Ich hoffe, dass bessere Impfstoffe und eine vernünftige Kommunikation dazu beitragen, dass dieses Fehldenken geändert wird." In Bezug auf unmittelbare Bedenken hinsichtlich der Auswirkungen des Coronavirus wendet er sich erneut der Frage der Zugänglichkeit zu: "Im Moment mache ich mir mehr Sorgen um Ebola. Es ist ein größeres Ausbruchsproblem und in einem Gebiet, das nur schlecht versorgt wird. Ich denke, China ist recht gut darin, medizinische Probleme zu lösen." Wenn Sie Ihr Team mit den Besten der Branche ausbauen möchten, wenden Sie sich an unsere Fachberater: Für unser deutsches Team rufen Sie bitte +49 30 217 899 21 oder +49 30 217 firstname.lastname@example.org. Wenn Sie auf der Suche nach Ihrer nächsten Herausforderung sind und einem innovativen, weltweit führenden Unternehmen beitreten möchten, haben wir möglicherweise eine Rolle für Sie. Hier finden Sie unsere neusten Jobs. Pandemic ist jetzt auf Netflix verfügbar. Anbei der Trailer.
31. March 2020