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Trust the worlds biggest data and analytics recruitment company to support your hiring or job seeking needs



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Harnham is one of the world’s leading  providers of recruitment services and advice  to the Data and Analytics marketplace 

We support global corporations through to ambitious local start-ups, so whether you need a Credit Risk Manager in London, a Data Scientist in New York, or a Head of Analytics in Frankfurt we can help you achieve your business goals.

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With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

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Weekly News Digest: 14th - 18th June 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics. Gov.uk: Five signs of a good data quality culture Particularly post-pandemic, we all want to know that our data is fit for purpose. In this article from the Government Data Quality Hub, they look at five ways to ensure that your data's quality is right for your's and your users’ needs. This includes: Everyone is involvedData quality is a commitment, not a taskYou know what works for your organisationYou know why quality mattersYou are proactive not reactive We know that committing to a good data quality culture is a continual process. This core advice allows us to take a step back and think about how you can understand your unique challenges and involve the right people, so you can prevent bad quality data before it damages your work. See more on this here. Analytics Insight: 5 types of artificial intelligence that will shape 2021 and beyond We really like this article from Analytics Insight that explores the future of technology, and specifically the rise in uses of artificial intelligence (AI). AI is often seen to be disruptive as there is an assumption that robots could take over and jobs are wiped out, but it’s more likely that humans and machines will work together to streamline processes across a range of industries. The different types of AI to keep an eye on include: Customised technology providerChoosy algorithmHuman-machine interactionReciprocating machinesTheory of mind We’re always excited to learn more about new technologies, click here to read more on this. KD Nuggets: Five types of thinking for a high performing data scientist In this piece KD Nuggets look at how the way our approach to problem-solving may be guided by your personal skills or the type of problem at hand. As a Data Scientist, appreciating different approaches can help you more effectively model data in the business world and communicate your results to the decision-makers. Whether this is model thinking, systems thinking, agent-based thinking, behavioural thinking, or computational thinking, taking the time to understand your approach will significantly help the way you complete the function of your role. To read the full article, see here.  TechRepublic: These 220+ courses will help you master tech skills and prep for IT certification exams We know that there is a digital skills gap. According to Boston Consulting Group, there will be tens of millions of job vacancies by 2030 that will be hard to fill because not enough workers have the required skills, many of which are in technology. One of the best ways to upgrade your skillset is to complete extra training and qualifications to ensure you’re always learning more about your market and providing yourself with the best opportunities to achieve your next career step. ITU Online has over 200 courses covering cloud deployment, cybersecurity and more. Of course, this isn’t the only way in which you can level up your skills, but it’s a good place to start! To read more about this, click here.  We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.    

How Will Embracing Flexible Working Help The Life Science Sector To Grow?

COVID-19 has drastically changed ways of working in the Life Science industry. Overnight, teams moved online, while new research had to be prioritised. Life Sciences were already moving towards more remote working, and the pandemic has only quickened this shift. There is no doubt these changes have fundamentally changed the Life Science sector and how professionals working in this space operate post-pandemic.  However, uncertainty still remains about the viability of remote working for the sector and there is a divide between those able to work remotely and those who need to go into ‘wet labs’. Is remote working a step too far for Life Sciences? Collaboration  2020 saw an increase in collaboration between professionals working across different areas of Life Sciences. Interestingly, organisations who may usually compete came together to share data and work towards a shared goal. Collaboration is essential in Life Sciences, yet for many, remote working reduces spontaneous teamwork and creativity.  New flexible lab spaces may be the future for Life Sciences though. RUNLABS have recently opened their first fully equipped flexible lab space in Paris for scientists and companies working in Life Sciences. This space hopes to builds on the existing collaborative approach in the industry and encourage further cooperative innovation. Efficiency  Many employees noticed a spike in employee efficiency when working remotely. By eliminating commutes and increasing flexibility, employees were able to be more productive with their time. Remote working also allowed organisations to streamline processes and reduce time spent in meetings.  However, insight from McKinsey highlights that research and development leaders estimate productivity has fallen by between 25 and 75 per cent due to remote working. Those in pharma manufacturing have reported lower levels off efficiency, as well as the potential for lower-quality outputs.  Research The pandemic forced remote trails to become a necessity, and since then, they have increased in popularity. While face-to-face research is still preferrable, remote trials can reduce costs and improve efficiencies. Indeed, on-site monitoring accounts for a significant portion of the costs of bringing a new product to market, yet this is no longer necessary in remote trials.   Not only are remote trials more cost-effective, but they can open research to a wider range of patients and can increase the communication between trial participants. Diversity Flexible working can run a risk to diversity and inclusion though. McKinsey also notes that, ‘when faced with a crisis, leaders often revert to relying on the core team of people they already know and trust. This disproportionately affects women and minorities because they are often not part of that group. Differences in perceptions and experiences of inclusion results in individuals or communities being disenfranchised, which can be devastating to careers and create a two-tiered culture.’ We know that 27 per cent of D&I leaders say their organisation have put all or most of their initiatives that embrace diversity and inclusion on hold because of the pandemic. However, remote work unlocks new hire pools and opens up the workplace to a more diverse workforce. Workers are no longer restricted by their geographical location or personal circumstances. Flexible working is an opportunity for Life Science organisations to harness a wider talent pool and increase their diversity. There is no doubt that Life Science is one of the most cutting-edge sectors globally and the pandemic has only cemented this. COVID-19 has shown the potential for remote working in life sciences, and in-person health care professional access may never return to pre-lockdown levels. But, going forward life sciences need to remember remote working is not practical for everyone nor every role. Organisations will need to consider individual wellbeing and role efficiency as they decide their next step.  If you’re in the world of Data & Analytics and looking to take a step up or find the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

Product Management: Quels Sont Les Outils À Utiliser Au Quotidien?

Lorsque nous parlons d'outils en Product Management, nous faisons généralement référence aux quelques outils standard que la plupart des chefs de produit utilisent quotidiennement. Ces outils de gestion de produits incluent généralement des logiciels d'analyse, des outils de tracking et des logiciels pour la roadmap produit. En plus de recueillir des informations sur les produits, de suivre le backlog et d'examiner la roadmap, il existe de nombreux autres outils. En tant que recruteur à Harnham spécialisé en Product Management, voici une liste d'outils pour vous aider à exceller dans votre rôle. Outils de gestion de projet  Les logiciels de gestion de projet d'aujourd'hui sont beaucoup plus robustes et offrent un moyen simplifié de suivre et de documenter en détail. À l'aide d'une application Web telle que Trello, par exemple, vous pouvez suivre et partager divers éléments avec les membres de l'équipe concernés en regroupant ces éléments dans des tableaux faciles à visualiser. D'autres outils de gestion de projet populaires incluent Microsoft Project, que les équipes organisent généralement au format de diagramme de Gantt, et Jira, qui est souvent configuré comme un outil de suivi des problèmes moins visuel. Outils de communication et messagerie  Lorsque le développement de votre produit, vous aurez besoin d'un moyen de communication simple et immédiat, que vous pourrez enregistrer et suivre dans le temps. Il existe de nombreux outils simples basés sur le cloud qui permettent ce type de communication d'équipe simple et centralisée. Slack et Atlassian's Confluence sont quelques-uns qui me viennent à l'esprit. Outils d'enquête client / Sondage Les outils de sondage Web comme SurveyMonkey ou Typeform, sont très utilisés. Ils ont l’avantage d’avoir des types de questions préformatées, de proposer des questions à choix multiples, des listes déroulantes ou simplement des champs de commentaires ouverts. La création d’un sondage est réalisée en quelques minutes. Vous pouvez ensuite envoyer le sondage à vos clients et suivre et analyser facilement les résultats. Petite astuce: Utilisez vos sondages avec parcimonie, afin de ne pas perturber votre base d'utilisateurs. Outils de suivi et d'analyse des utilisateurs Ces outils peuvent être des sources inestimables d'informations et de renseignements sur la façon dont les utilisateurs de votre logiciel ou les visiteurs de votre site Web interagissent réellement avec votre produit et votre contenu. Les outils intéressants à utiliser sont Pendo ou Amplitude par exemple.  En conclusion, le Product Manager dispose de nombreux outils à sa disposition pour gérer au mieux les différentes attentes à son sujet. Pour plus d’informations à ce sujet ou pour toute aide dans votre recherche de profils en Product Management, n’hésitez pas à me contacter ou visiter le site Harnham. 

Weekly News Digest: 7th - 11th June 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.   ITProPortal: How computer vision can help vaccine distribution scale securely This insightful article from ITProPortal demonstrates the importance of computer vision in medicine and logistics - particularly in regards to COVID-19 vaccinations. Everyday computer vision makes it possible for the transportation and distribution of vaccines to be carried out safely.  Some of the top points from the article were: Computer vision helps secure vaccine supply chains Automated procedures reduce vaccine loss and wasteDigital records can match citizens to test samples and vaccine batch  The pandemic has accelerated the digital transformation. The possibilities of smartphone and computer vision are endless, and will be vital in helping maintain the future population health. There is no doubt that this technology will continue to be critical in how we navigate the future.   To read more about this topic, click here.   Global Government Forum: Europe’s strategy for responsible AI and data will also boost digital transformation Although the pace of digital transformation within European governments has accelerated during the pandemic, there is a long way to go. A new AI Act hopes to accelerate the digitalisation of European governments and bring them into the modern age. The AI Act is one of the core elements of Europe’s broader digital and data strategies, and focuses on sharing storage and government of data.  Concerns over cultural attitudes and lack of understanding have previously delayed the digital transformation. But it is hoped this new legal framework will help accelerate the digitalisation of government in a holistic, responsible and sustainable approach. With clear data policies and the promotion of digital skills, this new legislative framework for AI and data may help European governments finally achieve their goal. To find out more about the AI act, read here. The Wire: Why scientists need to be better at visualising data Humans are visual creatures by nature, yet lack of training in data visualisation means scientists are not aware of its importance. As a result, poor data visuals can confuse readers and mislead scientist, reducing the quality and impeding the progress of scientific research. With scientific data becoming increasingly complex, scientists need to understand the importance of effective visualisation.   Key notions include: Bar charts are easiest to read but are not effective for visualising continuous dataPie charts are standard practice in some disciplines yet are cognitively challenging to analysis The choice of colour is crucial and can greatly impact understanding of the graph: if colour isn’t necessary, shades of grey are best There is a long way to go with data visualisation. To make visualisations effective, designers and scientists need to work with the brain, rather than against it.  To read the full article, see here. SearchBusinessAnalytics: How augmented analytics in healthcare improves patient outcomes This article explores both the benefits and problems of using augmented analytics in healthcare, with emphasis placed on the improvement of patient outcomes.  Of course, digital data in healthcare is not new. The current potential of digital transformation is huge. Intelligent use of augmented analytics creates better patient satisfaction and experience. And it doesn’t stop there. Using augmented analytics in clinical trials allow healthcare providers to identify the right populations and track responses.  However, without sufficient data literary, companies risk dealing with poor data quality resulting from a lack of diverse participants. Again, this is another example of the importance of data literary throughout organisations.  To find out more, click here. We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.    

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