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Data Scientist (m/f) in Berlin

commercetools

Workplace
Onsite
Hours
Full-Time
Internship
No
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Job Description

As a Data Scientist at commercetools, you will create innovative machine learning solutions for our cloud-based e-commerce platform. You will collaborate with a multi-disciplinary team of software engineers, product managers and analysts to build reliable prediction engines and generate data-driven insights. This is particularly suitable for data scientists who strive for diversity, as you will be working with a rich variation of data sources including images, natural language text, demographics, sales records or diverse sets of product attributes. We are an agile team that values iterative development and data-driven solutions to innovate the e-commerce sector and always deliver the best possible product.

 

Responsibilities:

  • Design and build scalable machine learning pipelines that 1) enable personalized and engaging customer experiences, 2) support efficient and elegant product information management for retailers, or 3) optimize internal operations and guide strategic decisions.
  • Make informed choices on preprocessing methods, feature engineering, and modeling techniques.
  • Communicate the results of your work not only in internal meetings, but also to the public (international conferences, blog posts, etc.).
  • Be a data evangelist and promote data-driven solutions through all departments of the company.
  • Stay up-to-date with new developments in machine learning research as well as e-commerce, and show initiative to create innovative solutions.

Requirements:

  • M.Sc. or Ph.D. in a quantitative discipline such as statistics, mathematics, computer science, physics, neuroscience, cognitive science or operations research.
  • At least 2 years of relevant work experience, either in business or academia.
  • Strong background in machine learning, programming, data mining and statistics.
  • Programming experience in scripting languages (Python, R, Matlab, or Julia) and machine learning libraries, preferably Python (pandas, numpy, scikit-learn, TensorFlow, etc.)
  • Ability to simplify complex results and effectively communicate them to people with different backgrounds.
  • Passion and natural curiosity to solve problems with data.
  • Aspiration to constantly improve yourself and learn new methods.
  • Excellent English language skills (German is a plus).
  • Bonus: Experience in e-commerce, Spark, Scala, NoSQL databases, computer vision, natural language processing, deep neural networks or data engineering.

What we offer:

  • Agile workflow and freedom to solve problems in your own way.
  • Option to attend (or organize) international conferences, meetups, hackathons, or workshops.
  • Challenging and meaningful projects in a company with over 10 years of history and a leader in the growing e-commerce business.
  • Highly motivated and qualified team that works with mutual respect and appreciation.
  • State-of-the-art-technology and modern offices in Berlin, Munich, New York and Durham.
  • Flexible, family-friendly working hours and the possibility of working from home.
  • Free coffee, tea, water, fresh fruits and some colleagues who really love baking cake.
  • Plenty of room to socialize, cook together, participate in running events, or play table tennis or foosball.

 
commercetools is the world’s leading platform for next-generation B2C and B2B commerce. To break the market out of being restrained by legacy suites, commercetools invented a headless, API-first, multi-tenant SaaS commerce platform that is cloud-native and uses flexible microservices. Using modern development building blocks in a true cloud platform provided by commercetools, customers can deliver the best commerce experiences across every touchpoint on a large scale.

commercetools has offices across the US, Europe, and Asia Pacific, with headquarters in Germany. Since its founding in 2006, commercetools software has been implemented by Fortune 500 companies across industries, from retail to manufacturing and from telecommunications to fashion.

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