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Le Marché Français


Le marché Français subit depuis quelques mois un peak d’activité en Data & Analytics. Les demandes pour des profils dans ce secteur croissent de jours en jours. Beaucoup de grandes écoles et d’écoles spécialisées ont suivi la tendance en créant des curriculums adaptés à ce marché en plein boom ; cependant les profils expérimentés demeurent très niche en France.

 

  JOB SPOTLIGHT

  Directeur Data Science - Paris, France

  Leader dans le développement Software
  depuis plus de 10 ans - cette société souhaite
  mettre en place une structure data Science
  efficace qui agira de manière transverses
  sur les divers départements de la société.

  SEE JOB


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La valeur ajoutée de Harnham

Basés à Londres, nos consultants sont tous natifs Français et ont évolué dans le recrutement en France pendant plusieurs années. Grace à notre connaissance du marché, ainsi que notre réseau très développé, nous sommes capables d’assister toute société dans leur recrutement dans le domaine Data & Analytics.

Notre force d’action est notre spécialisation; selon nos clients c’est une véritable valeur ajoutée d’échanger avec des consultants qui comprennent leurs besoins dans ce secteur en pleine croissance.

Que vous soyez une société qui recrute des nouveaux talents, ou un candidat à la recherche d’une nouvelle opportunité, n’hésitez pas à nous contacter proactivement pour discuter de vos projets.


RENTRONS EN CONTACT

Wesley Taupin au: +33 9 80 09 06 47 ou via mail wesleytaupin@harnham.com.

Harnham blog & news

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

Visit our Blogs & News portal or check out our recent posts below.

How to Succeed in Self-Service BI

Business Intelligence, along with Business Analytics and Big Data, is one of the terms often associated with decision-making processes in organisations.  However, there is little discussion around the importance of what skills decision makers in your organisation need to use the technology efficiently.  In recent years, the development of user-friendly tools for BI processes, Self-Service BI are increasing. Self-Service BI is an approach to BI where anyone in an organisation can collect and organise data for analysis without the assistance of data specialists. As a result of this, many businesses have invested in comprehensive storage and information processing tools. However, many are beginning to find that they are not able to realise the gains of these investments as they were expecting, may often due to underestimating the difficulties of introducing these systems into the current processes and transforming existing knowledge into actual actions and decisions.  In a worst-case scenario, if left unplanned, Self Service BI can sabotage your successful BI deployment by cutting mass user adoption, impairing query performance, failing to reduce report backlogs, and increasing confusion over the “single truth”. To prevent this from happening, here are our top three tips for ensuring the right implementation of SSBI in your company: UNDERSTAND YOUR USERS’ NEEDS There are three major user areas for analytics tools: strategic, tactical and operational. The strategic users make few, but important decisions. The tactical users make many decisions during a week and need updated information daily. Operational users are often closest to the customer, and this group needs data in its own applications in order to carry out a large number of requests and transactions.  Understanding the different needs of each group is necessary to know what information should be available at each given frequency to help scale the BI solution.  HARNESS THE POWER OF ADVANCED USERS To ensure a successful BI deployment, utilising advanced users is key. Self-service BI is not a one-size fits all approach. Casual users usually don’t have the time to learn the tool and will often reach out to ‘Power Users’ to create what they need. Hence, these users can become the go-to resource for creating ad-hoc views of data. Power Users are the ideal advocates for your business’ self-service BI implementation and should be able to help spur user adoption.  UPGRADE INTERNAL COMPETENCIES  Our final tip for a successful implementation is to communicate the new tool thoroughly to the users.  It is highly unlikely that employees who have not been involved in the actual development project will immediately understand what the tool should be used for, who needs it, and what it should replace. By upgrading internal competencies, you can avoid becoming dependent on external assistance. Establishing a cross-organizational BI competence centre of 5-10 members, who meet regularly to share their experiences will help drives and prioritise future use of the tool. The added benefit of a successful implementation is that it will generate new ideas from users for how the organisation can use data to make better decisions. If you have the skillset to implement Business Intelligence solutions, we may have a role for you.  Take a look at our latest opportunities or get in contact with our team. 

Elise Myhren

08. October 2018

Will Artificial Intelligence Revolutionise Eye Healthcare?

Faced with a rapidly expanding and increasingly older population, Healthcare resources in both the UK and US are facing an unprecedented level of demand. With only limited resource available, conversation is beginning to turn to the potential use of Artificial Intelligence (AI) to ease some of the strain. A recent example already seeing success is the current collaboration between Google’s DeepMind and London’s Moorfields Eye Hospital. But, as the lines begin to blur between human and machine-diagnosis, it’s worth questioning what role AI should actually play.  SEEING THE POTENTIAL IN AI Aside from the increase in population, there are many societal elements that are affecting the healthcare system. An increase in illnesses such as diabetes has led to a rise in eye-diseases and increased demand on optometrists.  Fortunately, AI can speed up the process with new technologies allowing systems like DeepMind to make their own diagnosis. Optical Coherence Technology (OCT) allows optometrists to create a 3D scans of people’s eyes. By bouncing near-infrared light of the interior surfaces of the eye, it can create an image that will reveal any abnormalities. DeepMind has been trained on over 15,000 scans and can now form a likely diagnosis, having used algorithms to find common patterns within the data.  Head of DeepMind, Mustafa Suleyman, says: “ [This could] transform the diagnosis, treatment, and management of patients with sight threatening eye conditions [...] around the world.” However, with an accuracy of just over 94%, there is still enough room for error to cause concern, especially given the potential consequences of an incorrect diagnosis.  LOOKING FOR MISTAKES  This doesn’t mean we should rule out the use of AI altogether. Whilst we may not be able to solely rely on the technology for diagnosis, it can be effective when working hand-in-hand with a human skillset.  In particular, by using AI systems for Triage purposes (determining what order patients should be seen in), as opposed to making a full diagnosis, patients demonstrating more significant symptoms could be reported and seen by a medical professional as priority, potentially leading to a higher chance of recovery.  When AI is used as a driver for patient management, as opposed to being viewed as alternative physician, it can create a faster and more efficient process.  To help continue to improve the results produced by DeepMind, the NHS have been given a validated version to use for free for the next five years. Using real-world applications over this time should streamline both their processes, and the technology itself.  A LONG TERM VISION For the time being, AI’s role within Eye Health is one of evolution, not revolution. With the inconsistency of current technology and the impact of incorrect results on people’s sight, it can only be utilised as a supporting tool.  For now, the skillsets of Data Analysts and medical doctors remain too separate to full work hand-in-hand. Add to this the risks of automation bias (a willingness to blindly trust a machine’s output), and the margin of error is too high.  However, that’s not to say that AI can’t and won’t play a significant part in the future of Healthcare. With the technology to detect eye conditions through the lens of your smartphone camera closer than ever to mainstream use, AI is set to play a huge role in outpatient treatment. At this stage, however, that role will be one of risk predictor, not eliminator.  If you think you have the skillset to help take AI to the next level in Healthcare we may have a role for you. Take a look at our latest opportunities or get in contact with our team. 

Nick Mandella

26. September 2018

Harnham's Brush with Fame

Harnham have partnered with The Charter School North Dulwich as corporate sponsors of their ‘Secret Charter’ event. The event sees the south London state school selling over 500 postcard-sized original pieces of art to raise funds for their Art, Drama and Music departments. Conceived by local parent Laura Stephens, the original concept was to auction art from both pupils and contributing parents.  Whilst designs from 30 of the school's best art students remain, the scope of contributors has rapidly expanded and now includes the work of local artists alongside celebrated greats including Tracey Emin, Sir Anthony Gormley, Julian Opie, and Gary Hume.  In addition to famous artists, several well-known names have contributed their own designs including James Corden, David Mitchell, Miranda Hart, Jo Brand, Jeremy Corbyn, and Hugh Grant.  The event itself, sponsored by Harnham and others, will be hosted by James Nesbitt, and will take place at Dulwich Picture Gallery on the 15th October 2018.  You can find out how to purchase a postcard and more information about the event here. 

Simon Clarke

17. September 2018

Breaking Code: How Programmers and AI are Shaping the Internet of Tomorrow

Data. It’s what we do. But, before the data is read and analysed, before the engineers lay the foundation of infrastructure, it is the programmers who create the code – the building blocks upon which our tomorrow is built. And once a year, we celebrate the wizards behind the curtain.  In a nod to 8-bit systems, on the 256th day of the year, we celebrate Programmers’ Day. Innovators from around the world gather to share knowledge with leading experts from a variety of disciplines, such as privacy and trust, artificial intelligence, and discovery and identification. Together they will discuss the internet of tomorrow.  The Next Generation of Internet At the Next Generation Internet (NGI), users are empowered to make choices in the control and use of their data. Each field from artificial intelligent agents to distributed ledger technologies support highly secure, transparent, and resilient internet infrastructures. A variety of businesses are able to decide how best to evaluate their data through the use of social models, high accessibility, and language transparency. Seamless interaction of an individual’s environment regardless of age or physical condition will drive the next generation of the internet. But, like all things which progress, practically at the speed of light, there is an element of ‘buyer beware’, or in this case, from ‘coder to user beware’. Caveat Emptor or rather, Caveat Coder The understanding, creation, and use of algorithms has revolutionised technology in ways we couldn’t possibly have imagined a few decades ago. Digital and Quantitative Analysts aim to, with enough data, be able to predict some action or outcome. However, as algorithms learn, there can be severe consequences of unpredictable code.  We create technology to improve our quality of life and to make our tasks more efficient. Through our efforts, we’ve made great strides in medicine, transportation, the sciences, and communication. But, what happens when the algorithms on which the technology is run surpasses the human at the helm? What happens when it builds upon itself faster than we can teach it? Or predict the infinite variable outcomes? Predictive analytics can become useless, or worse dangerous.  Balance is Key Electro-mechanical systems we could test and verify before implementation are a thing of the past, and the role of Machine Learning takes front and centre. Unfortunately, without the ability to test algorithms exhaustively, we must walk a tightrope of test and hope. Faith in systems is a fine balance of Machine Learning and the idea that it is possible to update or rewrite a host of programs, essentially ‘teaching’ the machine how to correct itself. But, who is ultimately responsible? These, and other questions, may balance out in the long run, but until then, basic laws regarding intention or negligence will need to be rethought. Searching for a solution  In every evolution there are growing pains. But, there are also solutions. In the world of tech, it’s important to put the health of society first and profit second, a fine balancing act in itself. Though solutions remain elusive, there are precautions technology companies can employ. One such precaution is to make tech companies responsible for the actions of their products, whether it is lines of rogue code or keeping a close eye on avoiding the tangled mass of ‘spaghetti’ code which can endanger us or our environment. Want to weigh in on the debate and learn how you can help shape the internet of tomorrow? If you’re interested in Big Data and Analytics, we may have a role for you. Check out our current vacancies. To learn more, contact our UK team at +44 20 8408 6070 or email us at info@harnham.com.

Eoin Pierce

13. September 2018

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