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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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3 Ways Machine Learning Is Benefiting Your Healthcare

With Data-led roles leading the list in the World Economic Forum’s ‘Jobs of the Future’ report, it is no surprise that Data Science continues to be the main driving force behind a number of technological advancements. From the Natural Language Processing (NLP) that powers your Google Assistant, to Computer Vision identifying scanning pictures for specific objects and the Deep Learning techniques exploring the capability of computers to become “human”, innovation is everywhere.  It’s unsurprising, then, that the world of healthcare is fascinated by the possibilities Data Science can offer,  possibilities which could not only make your and my life better, but also save several thousands of lives around the world. To just scrape the surface, here are three examples of how Machine Learning (ML) techniques are being used to benefit our healthcare.  COMPUTER VISION FOR IMAGING DIAGNOSTICS  Have you ever had a broken leg or arm and saw a x-ray scan of your fracture? Can you remember how the doctor described the kind of fracture to you and explained where exactly you can see it in the picture? The same thing that your doctor did a few years ago, can now be done by an algorithm that will identify the type of fracture, and provide insights into how you should treat it. And it’s not just fractures; Google's AI DeepMind can spot breast cancer as well as your radiologist. By feeding a Machine Learning model the mammograms of 76,000 British women, Google’s engineers taught the system to spot breast cancer in a screen scan. The result? A system as accurate as any radiologist.  We‘ve already reached the point where Machine Learning and AI can no longer just outsmart us at a board game, but can benefit our everyday lives, including in as sensitive use-cases as the healthcare industry. NLP AS YOUR PERSONAL HEALTH ASSISTANT  When we go to our GP, we go to see someone with a medical education and clinical understanding who can evaluate our health problems. We go there because we trust in the education of this person and their ability to give us the best information possible. However, thanks to the rise of the internet, we’ve turned to search engines and WebMD to self-diagnose online, often reading blogs and forums that will convince us we have cancer instead of a common cold.  Fortunately, technology has advanced to the point where it can assist with an on-the-spot (much more accurate) evaluation of your medical condition. By conversing with an AI, like the one from Babylon Health, we can gain insights into possible health problem, define the next steps we need to take and know whether or not we need to see a doctor in person.  There’s no need to wait for opening times or to sit bored in a waiting room. Easy access from your phone democratises the process and advice can be received by anyone, at any time.    DEEP LEARNING DRAWS CONCLUSIONS BETWEEN MEDICAL STUDIES Despite their extensive qualifications, even medical researchers can feel overwhelmed by the sheer amount of Insights and Data that are gathered around the world in hospitals, labs, and across various studies. No wonder it’s not uncommon for important Insights and Data to get forgotten in the mix. Once again, Machine Learning can help us out. Instead of getting lost in a sea of medical data, ML algorithms can dig deep and find the information medical researchers really need. By efficiently sifting a through vast amounts of medical data, combining certain datasets and providing insights, ML sources ways for treatments to be improved, medicines to be altered, and, as a result, can save lives. And this is only the beginning. As Machine Learning continues to improve we can expect huge advances in the following years, from robotic surgery to automated hospitals and beyond. If you’re an expert in Machine Learning, we may have a job for you. Take a look at our latest opportunities of get in touch with one of our expert consultants to find out more. 

Diversity In Data: An Overview Of Our Berlin Meet-Up

We started the year off right at Harnham Berlin, following the launch of our first ever European “State of Diversity Report” and working in collaboration with Smava to host an amazing event with three inspiring speakers on the topic. Our second event in Berlin, we wanted to continue with our mission to create a different type of tech meetup, moving away from purely technical discussions and focussing on important non-technical subjects within Data & Analytics and Recruitment. With Diversity & Inclusion more important than ever for both businesses and individuals, we wanted to do our bit to contribute to the discussion and talk about how the industry can move forward. As we were full on the day, and many of those who wanted to attend were unable to make it, I just wanted to put together a short piece on some of the highlights. Here are some of the top points covered on the day: Harnham’s State of Diversity Report David Webb – PrincipAL Consultant | Harnham As industry leaders, we feel it’s our responsibility to share our knowledge with businesses as individuals across the world of Data & Analytics. Alongside our annual Salary Guide, our Diversity report allows us to provide you with a comprehensive overview of the market and, in this presentation, we discussed the state of D&I in Europe and Germany specifically. Research has showed time and again that a diverse workforce drives profitability & increases staff satisfaction, so is it really surprising that having many people from different backgrounds can offer a company a broader range of solutions?Our report surveyed over 3,000 people and shows that not only can you increase profitability and improve staff satisfaction, a full TWO THIRDS of job seekers consider Diversity to be an important factor when analysing a job offer (which Bar Schwartz takes a closer look at during her talk).With a German workforce that’s only 25% female, there is still plenty of work to do in order to achieve greater equality. If you’d like a copy of the full report and want to talk through some of our findings in more detail, please just get in touch.  Everyone speaks about D&I, not everyone is ready for it Bar Schwartz – Head of Engineering | Signavio Diversity is not an outcome of hiring people of different gender or colour; it is an outcome of seeking and accommodating different personalities at work.Integrating diversity to your workplace or team requires education on what diversity is, what personality is, and how people differ. It requires challenging our biases on what the right ways to do things are and what is perceived as good or bad.It has to be a top-down, inside-out solution that covers everything from culture to leadership, every individual, and even your structures and roles. Change can start small. Integrating different people into the hiring process (even if they just observe), exposes people to profiles of diverse people and may challenge your unconscious biases. You can read more of Bar’s thoughts on creating a Diverse workforce here.  How the brain asks for Inclusion, not Diversity Kirsten Brueckner – CMO | mobile.de Our brain asks for inclusion, not diversity. Why? Our brain is incredibly smart in being as efficient as possible. This means that 95% of our decision making is unconscious and 70% of it is influenced by emotions (and we are great in post-rationalising). Most of the time we are on autopilot based on past experiences and knowledge and we don't even know this. We mix past experiences and knowledge with the input we get and form our own version of reality, which is a challenge in communication.What does that tell us about diversity? It’s difficult as we can't be on autopilot if we want to make progress. We need to discard past experiences and question our current knowledge. There are some simple tricks that transform recognising diversity into seeing inclusion; search for similarities (you will always find some), broaden your experience, be consciously conscious and enjoy the ride while learning. How to better advocate for Diversity & Inclusion Anna Mikulinska – CTO | Enterroom Why is it urgent to act? Without exposing the bias in Data, we use the inequality which will become a part of the design of the modern world and this is only amplified by the use of technology.How should we approach D&I? With empathy, and by addressing all the possible doubts Diversity & Inclusion raises. For Managers and Investors to spend money on supporting Diversity & Inclusion we need to make sure they truly understand the value of becoming advocates on their own. It’s not enough to convince someone for five minutes, they in turn need to be able to a buy in from their managers and partners as well. It’s time we stop avoiding difficult questions, let’s address them upfront.Everyone can act, but what can be done? Not everyone has to get on stage or into a board room. We can support progression with D&I by:Creating a D&I friendly work environmentBringing up the topic during the interview process as a potential candidateMentoring a young person willing to enter the Tech world and sharing your story with themNot being silenced by the argument “let’s not do politics” We will be running more events throughout 2020 which are already being planned and hope to see you all there! If you would like any more information, would like to get involved, or if you’re looking for support with your Data & Analytics hiring process, get in touch with our team of expert consultants and we will be able to advise you on the best way forward.  You can download our European Diversity Report here, and our Salary Guide here. 

Dave Farmer Appointed New Harnham CEO

I am pleased to announce that Harnham have named David Farmer as our new CEO.  David has been with Harnham since its inception in 2006 and has most recently being serving as COO. With the new appointment, I will be moving into the position of Executive Chairman.  On the move, David says: “I am thrilled to move into this new position at such an exciting time for the company. Having been with the business since the start, I am well aware of Harnham’s potential, particularly as the Data & Analytics market continues to thrive. We have an extraordinary team of home-grown talent at Harnham and I am eager to see where we can take the business next.”   David understands Harnham better than anyone and has dedicated an incredible amount of time and effort towards the success of the business. I cannot think of anyone better to lead us through the next stage of our growth.  This comes at an exciting time for Harnham with Partners Mark Bremer and Sam Jones stepping up to lead the London and New York offices, respectively. Additionally, long-term team members Ross Henderson and Talitha Boitel-Gill have been named Associate Directors and will oversee the growth of various teams within the UK business.  The global leader in Data & Analytics recruitment, Harnham now comprises of 160 people across four offices globally. 

How NLP Is Redefining The Future Of Tech

How NLP Is Redefining The Future Of Tech

During the last half of the past decade the importance of Data reached a level at which it was coined “the new oil”. This was indicative of a shift in the practices of individuals and businesses, highlighting how they now rely on something which isn’t measurable in gallons but in bytes. However,  because we can’t physically see the Data we generate, gather and store, its easy to lose our connection to it.  This is where NLP is comes into play. With the purpose of helping computers understand our languages, NLP (Natural Language Processing) gained an increased importance over the last couple of years. But, more than teaching a computer how to speak, NLP can make sense of patterns within a text, from finding the stylistic devices of a piece of literature, to understanding the sentiment behind it.  So, with NLP set to become even more prevalent over the next decade, here are some of the ways in which it’s already being put to use:  EXTRACTION Like an advanced version of using Ctrl + F to search a document, NLP can instantly skim through texts and extract the most important information. Not only that, but NLP algorithms are able to find connections between text passages and can generate statistics related to them. Which leads me to my next example: TEXT CLASSIFICATION  This is fairly self-explanatory: NLP algorithms can parameters to categorise texts into certain categories. You’ll find this used frequently in the insurance industry, where businesses use NLP to organise their contracts and categorise them the same way newspapers categorise their articles into different subcategories. And, closer to home, it’s similar algorithms that keep your inbox free from spam, automatically detecting patterns which are heavily used by spammers. But NLP does more than just look for key words, it can understand the meaning behind them:  SENTIMENT ANALYSIS Sentiment Analysis takes the above understanding and classification and applies a knowledge of subtext, particularly when it comes to getting an indication of customer satisfaction.  For example, Deutsche Bahn are using Sentiment Analysis to find out why people are unhappy with their experience whilst Amazon are using it to keep tabs on the customer service levels of their sellers. Indeed, Facebook have taken this one step further and, rather than just tracking satisfaction levels, they are examining how users are organising hate groups and using the data collected to try and prevent them mobilising.  With the advancement of Machine Learning and technological developments like quantum computing, this decade could see NLP’s understanding  reach a whole level, becoming omnipresent and even more immersed in our daily lives: PERSONAL AI ASSISTANTS The popularity of using personal AI-based assistants is growing thanks to Alexa and Google Assistant (Siri & Cortana not so much, sorry). People are getting used to talking to their phones and smart devices in order to set alarms, create reminders or even book haircuts.  And, as we continue to use these personal assistants more and more, we’ll need them to understand us better and more accurately. After decades of using generic text- or click inputs to make a computer execute our commands, this decade our interactions with computers need to involve into a more “natural” way of communicating. But these advances are not just limited to voice technologies. Talking and texting with machines, the way we would with friends, is increasingly realistic thanks to advances in NLP: CHATBOTS Since companies have realised that they can answer most generic inquiries using an algorithm, the use of chatbots has increased tenfold.  Not only do these save on the need to employee customer service staff, but many are now so realistic and conversational that many customers do not realise that they are engaging with an algorithm.  Plus, the ability to understand what is meant, even when it is not said in as many words, means that NLP can offer a service that is akin to what any individual can.  If you’re interested in using NLP to fuel the next generation of technical advancements, we may have a role for you. Take a look at our latest opportunities or get in touch with one of expert consultants to find out more. 

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