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MeasureCamp Berlin

MeasureCamp Berlin: A Preview

In preparation for this year's MeasureCamp Berlin, we sat down with Benjamin Bock, communications lead, to discuss what to expect, as well as his thoughts on the industry in general. Here's what he had to say: Can you explain MeasureCamp for people who haven’t been yet? MeasureCamp is an open, free-to-attend analytics 'un-conference' made by analytics professionals for analytics professionals (and everyone who wants to get there) around the globe. In that sense, it’s different to any conference you know of. Our schedule is created on the day of the event, and our speakers are fellow attendees. Listen to talks, give a talk, and discuss topics that really tickle your fancy. What can we expect at MeasureCamp Berlin this year? Let’s begin with what you can’t and never will expect at MeasureCamp Berlin: Sales pitch presentations. We’ve all been there… you are visiting a fancy, expensive conference and all you get is Heads of 'This n’ That' talking about what their team did, what they spent money on and that you should buy Product X to be as Data-driven as them (mind the cynicism). At MeasureCamp you can expect talks and discussion rounds by around 150 fellow experts, who all know the daily adventures of cleaning Data, setting up analytics or debugging tracking code or running mind-bending analysis first hand.  What is your best tip for someone that has never been at MeasureCamp before? Don’t rush it! MeasureCamp is about mingling with the analytics community as much as it is about the talks and discussion rounds. Pick a few talks that really interest you and use the rest of the day to get to know other attendees. Our awesome sponsors are also more than happy to talk to you. What is the best advice you got last year at MeasureCamp? On a personal level, I was able to get some really good advice when it came to data privacy topics. GDPR was still fairly fresh and nobody really knew if what they had done was actually enough to not get into trouble. That’s the kind of advice you only get if you have the chance to talk to other professionals face to face. On another note, what are the most sought-after skills and technologies currently used? I can only speak of my experience here. On a hard skill level and depending on the individual role, you need a solid understanding of web technologies (JavaScript, HTML, CSS) and tag managing systems to be able to implement tracking (plus some knowledge in mobile development when your focus lies on apps). When it comes to analysing and visualising Data, you should understand the tool you are working with and its underlying Data-structures. Being able to retrieve tool-agnostic Data with SQL and running more sophisticated calculations (e.g. with Python) has become more and more important over the last few years. But there are some softer skills, that should not be overlooked as well. As an analytics professional, you should never assume that your knowledge and language are common ground. You need to be a strong communicator, who is able to explain complicated concepts broken down to the absolute basics. In your opinion, what will be the biggest challenge in digital analytics in the next year? Two weeks ago, I would have answered “bringing web and app Data together”. Now that we know Google is working on that topic, it’s still a challenge, but one I am happy to tackle in the coming year. Digital Analytics is constantly changing. What do you expect to be the most talked about topic at MeasureCamp this year? As a Tracking Specialist with a focus on Google products, I’d love to hear some talks about Google Tag Manager Custom Templates. But my top guess is, that the newly released Apps and Web properties beta for Google Analytics will be the talk of the hour. MeasureCamp Berlin is an open and free-to-attend 'un-conference', taking place this year on the 28th of September. The final batch of tickets will be released on the 21st of August at 03:00 PM (CEST). Click here for more information and to get hold of your place. 

Where Tech Meets Tradition

Where Tech Meets Tradition

If you’re lamenting the decline of handmade traditional products, cast your cares aside. There’s a new Sheriff in town and its name is, Tech. Just a generation ago, children would leave the farm or the family business, go to school, and then move on to make their place in the world doing their own thing. Away from family.  Today, the landscape has changed and those who have left are coming home. But this time, they’re bringing technology with them to help make things more efficient and more productive. Is Tech-Assisted Still Handmade? In a word, yes. Artists still make things “from scratch”, except now technologies allow them to not only see their vision in real-time, but their customers, too. Have you ever wondered what the image in your head might look like on paper or in metal? What about the design of prosthetic arms and healthcare devices by 3D printers? You’re still designing, creating.  But just like any new technology, there’s still a learning curve. Even for cutting-edge craftspeople who find that sometimes, the line between craftsmanship and high-tech creativity may be a bit of a blur. Not to mention the expense for either the equipment required or being able to offer art using traditional tools at technology-assisted prices. Somewhere between the two, there is a trade-off. It’s up to the individual to determine where and what that trade-off is. Life in the Creative Economy One of Banksy’s paintings shredded itself upon purchase at an auction recently. AI is making music and writing books. Augmented Reality, Virtual Reality, and Blockchain all have their place in the creative economy from immersive entertainment to efficient manufacturing processes. Each of these touches the way we live now. In a joint study between McKinsey and the World Economic Forum, 'Creative Disruption: The impact of emerging technologies on the creative economy', the organisations broke down the various technologies used in the creative economy and how they’re driving change. For example: AI is being used to distill user preferences when it comes to curating movies and music. The Associated Press has used AI to free up reporters’ time and the Washington Post has created a tool to help it generate up to 70 articles a month, many stories of which they wouldn’t have otherwise dedicated staff.Machine Learning has begun to create original content. Virtual Reality and Augmented Reality have come together as a new medium to help move people to get up, get active, and go play whether it’s a stroll through a virtual art gallery or watching your children play at the playground.  Where else might immersive media play out? Content today could help tell humanitarian stories or offer work-place diversity training. But back to the artisan handicrafts.  Artistry with technology Whilst publishing firms may be looking to use AI to redefine the creative economy, they are not alone. Other artists utilising these technologies include:  SculptorsDigital artistsPaintersJewellery makersBourbon distillers America’s oldest distiller has gotten on the technology bandwagon and while there is no rushing good Bourbon, but you can manage the process more efficiently. They’ve even taken things a step further and have created an app for aficionados to follow along in the process. Talk about crafted and curated for individual tastes and transparency. It may seem almost self-explanatory to note how other artisans are using technology. But what about distilleries? What are they doing? They’re creating efficiency by: Adding IoT sensors for Data Analytics collection Adding RFID tags to their barrels Creating experimental ageing warehouses (AR, anyone?) to refine their craft. Don’t worry, though. These changes won’t affect the spirit itself. After all, according to Mr. Wheatley, Master Distiller, “There’s no way to cheat mother nature or father time.” Ultimately, the idea is to not only understand the history behind the process, but to make it more efficient and repeatable. A way to preserve the processes of the past while using the advances of the present with an eye to the future. If you’re interested in using Data & Analytics to drive creativity, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expect consultants to find out more. 

How Will New Financial Risk Regulations Affect European Banks?

How Will New Financial Risk Regulations Affect European Banks?

The financial crisis of 2007-2008 changed banking. The world moved from taking mortgage loans in our dogs’ names to introducing strict regulations for banks prohibiting them from giving out loans to “anyone” without assessing Risk properly. In 2010 the Basel Committee on Banking Supervision (BCBS) introduced BASEL III, a regulatory framework that builds on BASEL I, and BASEL II. This framework changed how banks and financial institutions asses risk. It introduced an Advanced Internal Rate Based Approach (Commonly known as the AIRB approach).  Now, the committee has introduced new changes and, by 2022, all banks and institutions will have to implement the revised IRB Framework, as well as new revised regulations for the standardised approach, CVA Framework and new frameworks for Operational Risk and Market Risk. So, what does this mean for those working Risk? Change Is Coming Change is inevitable, no matter what you do. If you work in Risk Management and Compliance, change is something you can expect to happen, often. As mentioned above, by 2022 there will be lots of changes. The Basel Committee calls this initiative the “finalised reforms”, or BASEL IV which builds on the current regulatory framework BASEL III. Quickly summarised, the changes limit the reduction in capital that effect banks IRB models.  This change is predicted to impact banks in Sweden and Denmark the most, with estimations that capital ratio will fall by 2.5-3%, far higher than the 0.9% expected for the average European bank.  So what does all this mean for Swedish and Danish banks?  What’s Happening Now? One of the main things that Swedish and Danish banks need to revise for these new regulations, are their internal models. The new regulations introduced a new definition of Probability of Default, measured through a model commonly known as a PD model. Effectively this means that every bank must “re-develop” their internal PD Models in the IRB approach. Consequently, we are already seeing a clear response from the banks in their strategies moving forward. It has already become quite apparent that many banks are looking to make IRB model development their focus for 2019-2020 and 2021. This has resulted in a boom in the hiring space for developers with experience in IRB Modelling and Credit Risk Modelling in general, which in turn has led to high demand in the face of the low supply of these types of candidates. Understandably aware of this, modellers are now looking to negotiate higher salaries.  What You Can Do  For candidates that hold the right experience, there are good opportunities at hand. If so inclined, they can utilise this chance to finally see if the grass actually is greener on the other side, or not. However, there are a couple of things worth considering before making a move.   Firstly, are you actually keen on switching jobs? Your skills are probably equally in demand at your current employer and, if you are having doubts about moving from the get-go, you may well be able to negotiate a rise without pursuing a new opportunity. However, if you are serious about finding something new, this is a great time to do so. The majority of banks have found that these new regulations are creating an unsustainable workload,  and are now looking for talent externally to expand their teams. This means that the experienced modeller can pretty much have their pick of the litter.  Furthermore, if you are a junior modeller, there are now plenty of opportunities for you to enter a niche area known for being exciting and innovative. So, wherever you are in your career, these regulatory changes  are likely to have a large impact and open up new avenues for you to explore.   We all know that regulations in banking and finance are now essential, we all agree, even if they can be a little frustrating. However, what people often fail to think of are the opportunities new regulatory requirements create. In the case of BASEL IV, we’re already seeing an increase in demand for strong talent, and a demand for people who are passionate about Risk Management and model development.  For businesses, new regulations also provide the chance to not only improve their teams, but to  create new models that can be utilised to optimise and automate. A lot of financial institutions are already aware of this and are using these models to gain competitive advantage over their competitors, as well as to stay one hundred percent compliant.  If you’re looking to build out you Risk Management team or take on a new Risk opportunity for yourself, 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. 

How Data Is Shifting Defence

How Data Is Shifting Defence

When looking at the cyber security measures in 2019 the outcome is uncertain. Threats come in the form of pariah states, extremely skilled individuals, and illiberal actors. However, what is certain is the leaps and bounds made in technology.  Before computers, defence documents were in government offices. By the Second World War this would progress onto secure sites, take Bletchley Park for example.   The real watershed would come years later in the Cold War. While there was no direct military action (aside from the proxy Korean and Vietnam War), this tension was illustrated elsewhere, with the space race and nuclear armaments to name but a few. Both sides went to extraordinary lengths to guard and seize intelligence through covert ops. As this classified information made its way onto computers and in turn brought about new risks. This theme continues to the present day; as technology improves, so do offensive and defensive capabilities.  Hard Power With the advancement in technology this has been used by militaries to take and saves lives. Only a matter of years ago aerial bombardment would have to involve putting pilots at risk, flying deep behind enemy lines. These days, a bombing run could be carried out anywhere in the globe with the ‘pilot’ not having to leave their chair. How? Through Unmanned Aerial Vehicles (UAVs). This removes any casualties to their pilots, using advanced systems in Computer Vision to operate across the globe.  The ethics of this remain debated and there are many who express doubts at the use of AI, fearing their destructive potential. Others, however, see this as necessary advancement.  Indeed, in asymmetric warfare, established states’ advanced technology is near enough untouchable. Take an example from the US Marines. Still in testing, an advanced platform can allow troops on the ground to see if a room has been cleared, saving friendly lives. This is way above the capabilities of rogue terrorist forces, and looks set to play a crucial role in saving lives. It would seem highly unlikely that the Taliban, for example, could use sophisticated weaponry to bring down a jet.  However, the danger in 2019 now lies with the established illiberal states who still pose a serious threat. It is paramount that nations continue to advance, to both deter and, if needed, counter a hostile force. Soft Power While NATO states have shown dominance in physical terms over past foes, 2019 brings uncertainty when it comes to soft power, most notably cyber-security. The threats to this are very real, and are a put civilians at risk - take the Sony and NHS hackings as an example.  Moreover, the notion of alleged election meddling continues to plague politics, notably the US 2016 Election and the Brexit referendum. There have been several accusations of state-sponsored foul play incorporating the use of bots to influence people’s decision making, mostly through continual pressure on either fake news or mass-support of certain decisions. They impact society directly into our homes, considering the popularity of social media platforms like Twitter and Facebook. Alongside many other nations, the UK is taking action to counter this type of threat. Only recently a specialist cyber-security division in the army has been established, quite literally to both counter, and if needed, launch cyber-attacks.   Ultimately, society has come a long way, physically and online when it comes to defence. Sophisticated weaponry continues to develop but is raising new ethical questions, particularly in regards to the use of AI and Computer Vision. Civilian institutions remain at risk, with many having been targeted in hacks or through intervention on social media. Threats may continue to evolve, but so will defence strategies, with the two competing to stay one step ahead of the other.   If you’re interested in applying Data & Analytics to national security, we may have a role for you. Take a look at our latest opportunities, or get in touch with one of our expert consultants to find out more. 

How movie studios use data

Lights, Camera, Data

Whilst Data continues to play a huge role in all aspects of life; developing businesses, schools, health care etc., one industry has already seen a massive impact from the Big Data revolution. The film industry, and its television counterpart, were among the first see to the potential of how Data can transform the way they work.  Beyond profit, access to new types of Data is allowing companies to consider what audiences will be most interested in at specific times, utilising current viewing habits, what topics are the most popular on social media, and even the news so they can create something that tailors to everyone’s different interests. The Streaming Revolution Netflix’s popularity is down to more than the variety of movies and series it has to offer. Its pioneering use of recommendation systems, originating when it was purely a DVD rental service, means that it always knows what its subscribers want to watch, when they want to watch it, and on what device. Their ability to tailor bespoke recommendations, down to which poster people see, has created an entirely different approach to how viewers chose and engagement with entertainment.  Netflix’s Data collection means that it knows its audiences very well, something they can utilise as part of their marketing. By contrast, even a behemoth like Disney can struggle to compete. Following the success of 2015’s Star Wars: The Force Awakens, Disney Chairman, Bob Iger admitted ‘we don’t have any idea who went to see Star Wars in the cinemas’. Whist this may have not been too much of a problem at the time, given the film’s $2 Billion box office, the diminishing returns of the films that have followed suggests that better insight as to why the film was a success may have been beneficial. It’s no wonder, therefore, that Disney are launching their own streaming service later this year.  Beyond Box Office In the majority of businesses these days, Data is used to decipher consumer buying habits, web traffic and social media interactions, as well as to monitor supply chains, costs and sales. This is no different for the movie industry, particularly when examining what makes a move work. By using Data Science, producers can determine which actors, directors, release dates and even running times are likely to make a movie profitable. For example, history may dictate that the summer is likely to be the most profitable time of year. Whilst this may be true for June, where average profit is $100m, ten times that of January, November and December are the second and third most profitable months.   Beyond assessing profitability, however, Hollywood is using technology to try and re-establish a relationship between creators and audiences. Newly emerging tools are empowering studios to convert massive quantities of movie-goer reactions into meaningful actionable insights. With Big Data analytics, movie executives have gained an insight into audience’s perspectives and this is dramatically altering the way in which movies are made, marketed and distributed. Companies like IBM are looking at new ways of tracking sentiment analysis that will have a massive impact on the creative process. However, whether or not the industry’s leading writers and directors will want to work within these parameters is yet to be seen.  #DataDrivenAds Data’s impact on the movie industry goes beyond the insights it offers on audience perceptions. When it comes to marketing a movie, the Data & Analytics space offers a number of opportunities. Studios are beginning to realise that, in order to drive the small-screen generation to the big screen, they need to come to their territory. To promote ‘The Dark Tower’ in Singapore, Sony ran a series of targeted mobile adverts that allowed users to choose a character to engage with. A follow up campaign then targeted users who had engaged with relevant messaging and details of showtimes at their nearest cinemas, using the mobility of their devices to their advantage. Furthermore, for the release of ‘Ready Player One’, Facebook offered an augmented reality experience for those who engaged with the film’s poster in public.  However, sometimes, the most effective marketing technique remains word-of-mouth. Netflix’s ‘Bird Box’ received little critical praise and minimal attention initially upon release. However, once users started posting memes about the movie onto their social media feeds, viewing figures picked up exponentially. This allowed Netflix to reassess their marketing efforts and respond to public sentiment, creating a strategy that fed off the zeitgeist and was significantly more effective.  Data has transformed the movie industry. If you’d like to work with Data & Analytics to transform another, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

Creating Your Own ‘Unicorn’ Employee

The elusive unicorn. Once a mythical beast, it is now a term for a new mythical creature; the unicorn employee. As Data fields transition from generalist to more specialised niches within the industry, businesses are realising the need for more agile and adaptable employees. However, there is a bit of a twist on the business end. It’s a mix of a diversified skillset and expertise. Though one seems at odds with the other, it doesn’t have to be. On the flip side, employees want development, citing it as the number one reason for leaving a business in our 2019 Salary Guide. So, we thought we’d take a look and see where the disconnect was. After all, if employees want development and businesses want diversification, couldn’t the two come together for the benefit of all?  In a word, yes. Investment in employees through reskilling and upskilling are two important and useful ways to create your ideal employee and placement. There’s no better return on investment. Let’s take a look at how finding your unicorn employee can add value to your business. Think Outside The Job Description While the job description offers a good guideline of what’s expected in your day-to-day role, it can’t predict the changes, trends, and other issues within your industry. And in the digital tech world, change is the name of the game. Businesses need someone who can react quickly and effectively. Employees need to have skills either to manage the job themselves or know when to reach out to team members for help. This can’t happen in a siloed situation.  A few traits of the unicorn employee include flexibility, a curious nature, excited about learning new things, and the openness to offer suggestions within and across teams.  In a recent LinkedIn article, Hootsuite CEO Ryan Holmes captured it best. “Like actual unicorns, they’re hard to find, but once hired, offer up enormous benefits in the workplace. To name a few, they shatter expectations, raise the bar for everyone and are simply a joy to be around. Unicorn employees can literally take your business to the next level.” If you’re looking to hire a unicorn employee, look beyond their resume. While it’s a tool and will offer skills the employee has now, it can’t show you whether or not he or she will go the extra mile. And like the mythical beasts, these unicorn employees may come from surprising places, be open to new possibilities and think beyond the job description.  How to become a Unicorn Employee Be Coachable. Have a growth mind-set, a desire to learn, and find every opportunity to upskill. This is lifelong learning at its finest.Be a hard worker, but know when to rest and recharge.Raise the bar as a teammate and encourage others to do the same. Raise your Emotional Intelligence. Demonstrate empathy, be aware of your emotions and your teammates’, and help motivate others. How to Attract and Retain Top Talent As you plan your next level of hire in search of the not-so-elusive ‘unicorn’ employee, consider these few steps to get you on the right track. Understand job roles. The job beyond what’s on paper. See what it’s like on the other side and make assessments from the point of an employee. What’s their day-to-day routine, touchpoints, and technology turn-ons to help them do their job?Employee experience and technology are forever entwined. What tech skills do your potential employees have and what would they like to learn? Does their curiosity spark yours? Broaden your range. Encourage employee participation in technology decisions and include people from a wide range of levels and departments. Let them help with planning, selection, and design. After all, who better than those who use it and know it inside and out?To upskill is to create lifelong learning opportunities through classes and beyond. Other ways to upskill include exploring new mind-sets, developing diverse relationships, and redefining how people work. These few suggestions scratch the surface. Though, Gartner does offer these strategies in competing for talent. The demand for top talent and the scarcity of it hasn’t diminished, but with a few tweaks to your planning strategy, you can lay the groundwork for attracting great employees. If you’re an employee hoping to broaden your range, open to new technologies as well as reaching out in a department not your own, and a team motivator. You might be a ‘unicorn’ employee. Somewhere between the two, we hope you’ll meet and in next year’s guide, development and diversification won’t be quite as at odds with each other. Companies need to remember candidates are stakeholders in the hiring process. Candidates need to remember sometimes it comes down to education. Educate the company how you can best serve them. That question they ask – why do you want to work for this company? This is where you ‘wow’ them and educate them to your why. Be flexible in your hiring and consider flipping from top-down to manager-centric in a bottom-up approach. After all, who is better positioned to offer insights into how jobs are changing and the skills required for it. If you’re looking for a unicorn, or to make your mark on a company, check out our current vacancies or get in touch with one of our experts consultants to learn more. 

Data & Analytics in Munich

Three Reasons Why Munich Is The Place To Be For Data Analysts

As one of the world’s largest economies, Germany continues to attract tech talent from all over the world, and has even overtaken the UK in terms of intra-Europe tech immigration in recent years. Whilst Berlin may be the first place that comes to mind when thinking of places to live as a Data Analyst in Germany, with its numerous start-ups and international culture, there are several reasons why you should also consider the southern gem of Munich. Here are three of the best: A First-Class Quality Of Life While the first thing that comes to mind when thinking of Munich is often the world famous Oktoberfest and the beer induced crowds packed into small beer tents paying the equivalent of a year´s salary for a pint, this is not the only thing Munich has to offer. During the other 349 days of the year when Munich is not packed with Lederhosen-wearing crowds from all over the world, it is a tranquil, green place to live.  Munich is home to a number of large parks, including the beautiful Englischer Garten, Museums and a number of non-beer related cultural events throughout the year. It’s also the third largest city in Germany and, as such, has all the benefits that big city life has to offer. However, nature is never far away, with a beautiful mountain landscape just on the horizon, including the tallest mountain in Germany, the Zugspitze, which sits only 90 km away. On top of this, the transportation system in Munich is one of the best in the country; clean, efficient and so simple to use, it actually makes commuting bearable.  Expansive Opportunities  Most major European cities have seen a boom in the tech market in recent years and Munich is no exception. Not only home to some of the biggest global and German players such as Amazon, MunichRE, Man, Allianz and Linde, the city is also seeing an increasing amount of investment in tech start-ups.  This has led to tech talent, particularly Data & Analytics talent, being highly sought after by a number of the country’s biggest and best employers. And healthy competition means even healthier salaries. Even though Munich doesn’t have the lowest cost of living around, the average pay for Data Analysts is higher than in most other German cities, meaning you’ll get to make the most of your time away from the office.  A Thriving International Culture With 25-38% of Munich´s residents originating from other nations, more and more companies, big and small, are open to welcoming English speakers into their teams. While the culture in Munich still makes it easy to immerse oneself into the German language and culture, the city is also very welcoming to its international inhabitants.  Of course not everyone can speak English, but it is surprising how many people do. This makes getting around as a non-German speaker that much easier, especially considering that the Bavarian version of German can sometimes feel like a completely different language to what is spoken by the rest of the country.  Like every country, different cities attract different personalities and find the right place for you is crucial before making a move. But, with its high quality of life, great job prospects and international culture, Munich certainly has a lot to offer for any Data Analyst looking to move to or within Germany.  If you’re considering making a move to Munich, take a look at our latest opportunities, or get in touch and we can discuss what could work best for you. 

Our New Berlin Office

We've launched two new offices

I'm incredibly pleased to announce that this week we have launched two new offices.  The first, in central Berlin, will solidify our on-the-ground presence in the German capital and allow us to continue to develop our client base in this rapidly-growing market. Run by Senior Manager Peter Schroeter, under the guidance of our Director of Europe, Alex Hutchings, we're really excited to see the new space become a hub for Berlin's Data & Analytics talent.  Secondly, we've also opened a second Wimbledon office. Despite only moving in to our current home 18 months ago, our rapid growth has led to us opening an additional Executive Office to house our Operations team as we bring in more and more expert consultants. Fortunately, it's just over the road, so there's no need to grab a bus between meetings.  This continues to be a great time for Harnham and watch this space for more growth news in the not too distant future. 

Machine Learning: How AI Learns

Machine Learning: How AI Learns

Amazon has begun curating summer reading lists. How? Patterns. Facebook shows you ads for items you may have been searching for online. How? It learns from your browsing habits. Ever wondered how Facebook knows you were just looking at that pair of shoes or that particular guitar. The Data you feed it, feeds its brain. In other words, this is how Artificial Intelligence learns. Machine Learning. Whilst it can be disconcerting to know that a machine understands our buying habits, that’s not the only thing it’s used for. It’s also a pivotal tool in such areas as Bionformatics, Biostatistics, Computational Biology, Robotics, and more.  What is Machine Learning? Ultimately, it’s a method of Data Analysis which helps to automate model building and is part of Artificial Intelligence. In other words, it helps to solve Computational Biology problems by learning from Data to identify patterns and make decisions with little human intervention. This helps scientific researchers learn about many aspects of biology. However, running a Machine Learning project can be difficult for beginners, who may experience issues when trying to navigate the information without making mistakes or second guessing themselves. This is one of the reasons a Computational Biologist might want to upskill with a course or two in Machine Learning for a more robust understanding of the information being learned and applied.  The Good News and the Bad With each shift of industrial revolution, there has been one system which has made an indelible mark on our daily lives and the Fourth Industrial Revolution is no different. Just like we can no longer imagine factories without assembly lines, we can also no longer imagine not having Siri, Google Maps, or online recommendations. But, as exciting and as important as these things are, Machine Learning has become so crucial to our daily lives, so complex, it takes a technology expert to master it leaving it nearly inaccessible to those who could benefit from it. Why is Machine Learning Important? By building models to peel back the layers and discover connections, organisations can more easily and more quickly make improved decisions with little to no human intervention. Computational processing is both more affordable and more powerful. It’s possible to quickly scale and produce models which can analyse bigger and more complex data and there’s also a chance to identify opportunities and to help avoid any unknowns such as risk. Machine Learning is used in every industry from Retail to Financial Services to Healthcare. Here are just a few ways it has already transformed our world. Retail – Retailers are able to learn from their customers buying habits, predictive buying habits, how to personalise a shopping experience, price optimisation, and customer insights.Financial services – Machine Learning helps to prevent fraud and identify Data insights.Healthcare – Wearable devices allow for real-time data to assess a patient’s health. Medical professionals can also more quickly find red flags which can help improve diagnoses and treatment.Oil and gas – It cannot only help find where oil might be, but also predict refinery sensory failure, and streamline distribution.Transportation – Help to make routes more efficient and predict problems that could affect the bottom line. While humans can create at least one or two models a week; Machine Learning can create thousands.  Ultimately, the goal of Machine Learning is to understand the structure of Data. As it learns to determine what Data is needed for its structure, it can be easily automated and sift through Data until a pattern is found. This is how machines learn. If you’re looking to take your next step in the field of Machine Learning, we may have a role for you. Take a look at our latest opportunities, or get in touch to see if we can help you take that next step.

How to get ahead in Risk Analytics

How To Get Ahead In Risk Analytics

In the world of Risk Management, top talent is always in high demand. Despite this, those who specialise in area know that progression can be difficult and, according to our 2019 Salary Survey, is the slowest in the industry. So, how can you differentiate yourself from the competition, and what steps can you take to make yourself the ideal candidate for that promotion or new job you’ve been hunting?  Whether you are looking to move somewhere new, or trying to climb the ladder in your current company, here are some ways that you can make sure you stand out.  Stay one step ahead in tech Traditionally, the Risk Analytics tech stack has comprised of SAS, SQL and VBA. SAS and SQL remain very much present, but we are also seeing a clear increase in the use of Open Source programming languages, such as R and Python. Unsurprisingly, a lot of Risk Modellers and Analysts are now spending their time in developing their skills in these languages. One might argue that if you know one language, there’s not too much work required to upskill in another when you take on a new role, but this isn’t necessarily true. By being proactive and evolving your skillset in your current position, your CV will have a much bigger impact when it lands on a Hiring Manager’s desk.  Over the past few years, we’ve also seen the arrival of Machine Learning and AI in the world of Risk. Whilst many businesses are still slow to embrace these technologies, do not be surprised to see them make a big impact over the next couple of years. Risk Analytics are catching up to the rest of the industry in regards to technology, and having the knowledge and skillsets required in these areas before they take off will only enhance you profile.  Business-driven Data  In the world of Risk Analytics, it is easy to think that if you have the right programming and analytical skills in the right tools, you’ve all got all you need. You might be off to a really good start, but there’s more to it than that. It about having the balance.  Yes, being data-driven and understanding complex model development is crucial to becoming a good performer in this industry but, what truly separates the good from the great, is business acumen. The ability to understand both what your analytics and models do, and how they impact the overall business is now at the top of most Hiring Manager’s lists.  A person with good quantitative skills will always see something that can be improved, but they also need to know when to stop and be happy with the result. The key to getting this right lies in their understanding of the business and the ability to answer questions like “If I sit and work on this for 8 more hours, will the real-world difference be worth that amount of time and resource?”. By viewing things through the prism of cost vs reward, and understanding that balance, you can demonstrate that your value to a business goes beyond your analytical skills.  React, adapt and attract In this world there are a few things we can take for a certainty; the sky is blue, it will rain on your day off, and there will always be new regulations for financial institutions. Because of the certainty of change, a key thing employers look for in candidates is the ability to react quickly and make changes as soon as they are needed. Fast growing companies such as Klarna, tink and iZettle may seem like fairy-tale success stories, but the real edge they have is their adaptability and agile culture. Whereas some traditional corporations and banks have lengthy and complicated processes required before they adapt to new regulations, these new companies embrace their agility and get things done.  The ability to be agile and adaptable is, therefore, something that a lot of businesses are starting to realise is key. Therefore, if you’re looking to get ahead, you should try to evolve these qualities in your working ways. If you are looking for something new, look to prove you are driven and do not fear change. If you can demonstrate that you are able to work with a business-oriented mindset and embrace change, you’ll stand out as a key player in your team.  Specialist vs Generalist  With the world of Risk Management offering a number of opportunities to become very specialised in very niche areas, it’s worth considering whether this approach is right for you. There are some definite pros, for example, if you are the best developer of PD models for non-retail, you will be highly sought after for roles in this area. Plus, high demand, and a shortage of skillsets means that you will be in a good position to seek a high salary and lots of benefits. However, this does mean that you are likely to only have the opportunity to work in this area for the foreseeable future and, for some, this can become repetitive and not provide enough of a challenge. Additionally, if you were ever were to apply to work in a new area because of this, you would likely find yourself overpriced and needing to take a step down in seniority.  The alternative, therefore, is to become more of a generalist, with a broader, but less advanced skillset. Think being able to play every instrument, but only knowing one song. There are definitely some clear benefits with this approach, not least the ability to work on a diverse set of projects, gain an excellent understanding of how Risk Management affects a business on every level, and be able to slot into a number of roles easily. You will also gain a better idea of which areas of Risk that you like, and which parts you dislike. Whilst many analysts begin as generalists before looking to specialise when they get promoted, they often find that their knowledge will not be as deep as their specialist counterparts. Therefore, it is likely they will have to take a step-down or make a sideways move before they can achieve that promotion.  There is no right or wrong when it comes to the specialist vs generalist argument. However, for those looking for faster progression early-on, a generalist approach may be better suited despite the fact that you may need to change approach before reaching the most senior levels.  Whilst demand will always be high for the best candidates, competition for promotions and senior roles in Risk Analytics remains fierce. Therefore, by proactively thinking about the ways that you work, how effective you are, your business focus, and what your ambitions are, you should be able to get the most out of your career.   If you’re looking to get ahead in Risk Analytics, we may have a role for you. Take a look at our latest opportunities, or get in touch to see if we can help you take that next step. 

MeasureCamp Paris 2019

A few weeks ago, I was lucky enough to attend the sixth annual MeasureCamp Paris. It was Harnham's second time sponsoring the event and is always an amazing opportunity for us to get face to face with Digital Analysts not only from France, but all over Europe. Once again, the place was filled with industry-leading minds, all of whom were passionate about sharing their knowledge and the day-to-day challenges they face. As you'd expect, it was a pleasure to have the chance to see some familiar faces and get to talk with a variety of professionals about the market and share our thoughts. Their insights were unbelievably valuable. Fortunately, we were able to give them a sneak peek of our new 2019 Salary Guide and discuss our findings alongside some general market trends.   One particularly interesting point of discussion surrounded how double the amount of professionals are using the Google stack of tools compared the to the Adobe equivalent. Many commented on what they see as a lack of training and investment within their company in other Analytics tools (e.g Adobe) or CRO tools (e.g. AB Tasty, Optimizely, even Kameleoon) compared to UK and Nordic enterprises. Outside of this, there were a number of discussions on how the Digital Analytics space is evolving, especially on the impact that diversified Web Analytics roles are having on the industry, and how secure professionals feel in their positions as a result of this. With many commenting that a lack of career progression is making them feel unsure of their current role, it may explain why our Salary Survey found that 80% of the Data & Analytics professional are open to potentially leaving for the right opportunity.  This year's MeasureCamp Paris was both bigger and better. It's clear that Digital Analysts remain incredibly thirsty for new ideas and ways to upskill and so it's no surprise, particularly from what we saw on the day, that the market and talent pool are stronger than ever.  If you'd like to discuss any of the trends I've mentioned above, or are looking for a new opportunity, do not hesitate to get in touch with me here. 

The Harnham 2019 Data & Analytics Salary Guide Is Here

We are thrilled to announce the launch of our 2019 UK, US and European Salary Guides. With over 3,000 respondents globally, this year’s guides are our largest and most insightful yet.  Looking at your responses, it is overwhelmingly clear that the Data & Analytics industry is continuing to thrive. This has led to an incredibly active market with 77% of respondents in the UK and Europe, and 72% in the US, willing to leave their role for the right opportunity.  Salary expectations remain high, although we’re seeing that candidates often expect 2-10% more than they actually achieve when moving between roles.  Globally, we’ve also seen a change in the reasons people give for leaving a position, with a lack of career progression overtaking an uncompetitive salary as the main reason for seeking a change.   There also remains plenty of room for industry improvement when looking at gender parity; the UK market is only 25% female and this falls to 23% in the US and 21% across the rest of Europe.  In addition to our findings, the guides also include insights into a variety of markets and recommendations for both those hiring, and those seeking a new role.  You can download your copies of the UK, US and European guides here.

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