DATA SCIENTIST - GERMAN SPEAKING

Paris, Île-de-France
€40000 - €45000 per annum

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DATA SCIENTIST (DEUTSCHSPRACHIGE ROLE)

PARIS, FRANKREICH

40.000€ - 45.000€

Hast du schon immer geträumt in Paris zu arbeiten in einem Unternehmen wo du sowohl deine Deutsch- als auch deine Englisch Sprachkenntnisse benutzen könntest? Hast du gerade deinen (Master) Abschluss erhalten und möchtest dich im Bereich Data Science spezialisieren? Dann bist du hier genau richtig!

Nach zwei erfolgreichen Finanzierungsrunden (+ 40 Millionen€) sucht unser Kunde, ein fünfjähriger Start-up in der Versicherungsbranche, einen deutschen Data Scientist für sein Data Science-Team in Paris.

DIE ROLE

Als Data Scientist wirst du die Möglichkeit haben mit verschiedenen Kunden in deutschsprachigen Ländern zusammen zu arbeiten und gleichzeitig auch:

  • Fundierte Kenntnisse in der Codierung und Programmierung von Algorithmen gewinnen
  • Bei der Konzeption und Entwicklung von Lösungen zur Erkennung von Versicherungsbetrug und -Fehlern teilzunehmen
  • einem Team von +40 Datenwissenschaftlern beitreten
  • gelegentlich zu den Kundenstandorten reisen, um ihre Lösungen zu implementieren
  • die Beziehung zu deutschen Kunden verwalten
  • An spannende Projekten im ML/DL Bereich zu arbeiten und Dinge zu bewegen

DEIN PROFIL

  • Master- oder Ingenieurstudium in angewandter Mathematik oder anderen ähnlichen quantitativen Bereichen
  • Idealerweise Erste Erfahrungen in Data Science und Machine Learning
  • Gute Kenntnisse in JAVA, C / C ++ oder C#
  • du führst deinen Job mit Leidenschaft und Ehrgeiz aus
  • Muttersprachler Niveau Deutsch und sehr gute Englisch Kenntnisse

BEWIRB DICH JETZT!

Bitte melde dein Interesse an, indem du deinen Lebenslauf über den Link "Bewerben" auf dieser Seite sendest.

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10028EQ
Paris, Île-de-France
€40000 - €45000 per annum

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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 BRANDS USE DATA TO CREATE SUCCESSFUL CAMPAIGNS

Make no mistake: making minor adjustments to an ad or campaign that’s meant to appeal to the masses just won’t cut it. Customers crave creativity. They want to be understood. Which is why people respond best to brands that do their homework, doing their research into what appeals to different groups. How should businesses appeal to their chosen segments, then, considering how diverse people are? Data, of course. Why Data? For one thing, it drives results and creates improved outcomes. Data also helps to prove the value of marketing, providing a bargaining chip for future budget discussions. And, most rewarding of all, brands get valuable insights into their target market. Which, in turn, leads to more well-targeted, profitable campaigns.  And if you think Data doesn’t belong in the world of creative campaigns, think again. As OpenJaw Technologies Chief Marketing Officer Colin Lewis argues: “Creativity is not just compatible with being Data-driven – Data can drive better creative.” Psychological profiling Strategic communications consultancy, Verbalisation, researches and analyses language to form valuable insights. Using its Rapid Audience Insights Diagnostic system, the company’s team of psychologists and researchers work out how an audience thinks. They also learn the actual words an audience uses, which they then use as the basis of a marketing strategy.  Based on their unique research and insights, Verbalisation has created several successful campaigns for high-profile brands. These include the #NotAnotherBrother campaign for counter-terrorism organisation Quilliam, which looked at the motivations of jihadists.  The campaign is now used by the UN and schools across the UK, as well as the US Department of Defense. It is the most viewed counter-extremism campaign of all time, with more than half a billion global media impressions.  Location, location, location Out-of-home (OOH) advertising. Yes, it goes way back, but it’s actually the only traditional advertising channel posting rapid growth. In fact, thanks to mobile-location Data, brands can target audiences quicker and with a greater chance of success than ever before.  Great news for JCDecaux (JCD), a leading OOH company with ads reaching 410 million people in over 4,000 cities. JCD now works with location Data to define and segment audiences. Doing so helps it decide where to place media, improve campaigns and measure resulting store footfall and purchases.  Knowledge, so they say, is power. Particularly when that involves knowing the whereabouts of the most coveted customers. Newly teamed up with identity resolution company, Neustar, JCD’s insights look stronger than ever. JCD can now understand which of its locations rank higher for any brand’s most desired audiences. All thanks to location Data and real-time behaviour analysis.  Personalised employee training Data doesn’t just boost the results of B2C brands; it can also be a vital shot in the arm for internal security training campaigns. Training provider, CybeReady, for instance, uses a Data science-driven approach to deliver cyber awareness training with a difference: its anti-phishing platform helps security teams quickly roll out and tailor campaigns to individual employees. In big companies, getting employees up to speed is especially challenging. With many locations, languages and time zones to contend with, Information Security teams have their work cut out.  CybeReady eliminates these challenges by delivering 12 personalised, 60-second simulations to each employee. In their first language, every year. What’s more, the training provider uses machine learning to analyse performance on a daily basis. This enables it to provide the most appropriate simulations to each individual. The result? IT teams save 160 hours each month and employee resilience increases five-fold. There’s no limit to what Data can do. If you’re a fan, we may have a role for you. Take a look at our latest opportunities or get in touch with our expert consultants.  

The Evolution Of The Data Engineer

Every Data Science department worth its salt has at least one engineer on the team. Considered the “master builders,” Data Engineers design, implement and manage Data infrastructure. They lay down digital foundations and monitor performance. At least, that’s what they used to do.  Over the last few years, the role has shifted. Data Engineers have gone from mainly designing and building infrastructure, to a much more supportive and collaborative function.  Today, a key part of the engineer role is to help their Data Analyst and Data Scientist colleagues process and analyse data. In doing so, they are contributing to improved team productivity and, ultimately, the company’s bottom line. THE IMPACT OF THE CLOUD In the past, a Data Engineer would often move data to and from databases. They’d load it in a Data Warehouse, and create Data structures. Engineers would also be on hand to optimise Data while businesses upgraded or installed new servers.  And then along came the Cloud.  The rapid dominance of cloud computing meant that optimisation was no longer needed. And as the cloud made it easy for companies to scale up and down, there was less need for someone to manage the data infrastructure.   The collective adoption of the cloud has had a big impact on the function of Data Engineers. Because, provided a company has the funds, there is no longer the same demand for physical storage. Freed from endless scaling requests, engineers have more time to program and develop. They also spend more time curating data for better analytics.  AUTOMATING THE BORING BITS  Less than a decade ago, if start-ups wanted to run a sophisticated analytics program, they’d automatically hire a couple of Data Engineers. Without them, Data Analysts and Data Scientists wouldn’t have any Data. The engineers would extract it from operational systems, before giving analysts and business users access. They might also do some work to make the Data simpler to interpret.  In 2019, none of this extraction and transformation work is necessary. Companies can now buy off-the-shelf technology that does exactly what a Data Engineer used to do. As Tristan Handy, Founder and President of Fishtown Analytics, puts it: “Software is increasingly automating the boring parts of Data Engineering.”  STILL SOUGHT-AFTER  With automation hot on the Data Engineer’s tail, it can be tempting to ask whether they are still needed at all.  The answer is: yes, absolutely. When recruiting engineers, Data Strategist Michael Kaminsky says he looks for people “who are excited to partner with analysts and Data Scientists.” He wants a Data Engineer who knows when to pipe up with, “What you’re doing seems really inefficient, and I want to build something better.” Despite the rise in off-the-shelf solutions, engineers still play a key role in the Data Science team. The difference is simply that their priorities and tasks have shifted.  Today, innovation is the watchword. The best engineers are hugely collaborative, helping their teams go further, faster. It’s an exciting time to be a Data Engineer. If you’re interested in this field, we may have a job for you. Take a look at our latest opportunities or get in touch with our expert consultants.  

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