Senior Applied Scientist

One of Europe’s leading eCommerce companies, known for their effortless and very customer centric services with online shopping, are looking for a talented Senior Applied Scientist!

They are headquartered in Berlin and have tech hubs and offices across the world. They’re currently serving more than 31 million consumers, working in 17 markets, and processing more than 2.4 million payment transactions a day!

A startup at heart, they strive for the constant development of new ideas. With a critically acclaimed, game-changing technology focused on payments within the eCommerce market, they’re already an acclaimed company when it comes to setting the bar from a technological perspective.

Want to be part of a team where you will impact the lives of millions and join an organisation that places tech first? Then read on!

 

WHERE YOUR EXPERTISE IS NEEDED

  • Creating predictive models of customer issues to identify the customers who can proactively be helped.
  • Collaborating with software engineers to translate ML prototypes into production systems.
  • Collaborating with product managers and other stakeholders to identify new areas of potential impact.
  • Research challenging problems, such as improving the prediction of customer pain points. 
  • Querying, analysing data, and setting up monitoring and data quality assurance

WHAT WE’RE LOOKING FOR

  • Excellent educational background (minimum M.Sc) in Computer Science, Mathematics, Statistics or other similar quantitative field
  • At least 3 years of industry experience with Python and ML-related libraries such as pandas, scikit-learn, TensorFlow, Keras, XGBoost and big data frameworks such as Spark, Dask, Strong understanding of machine learning methods and  techniques, especially for customer behavior analysis and prediction
  • Deep understanding of statistics,  machine learning, and knowledge of best practices in productionalizing machine learning systems
  • Experience in building and maintaining data pipelines and collecting data from multiple sources and formats, and working with data science based services that provide an API

PERKS AT WORK

  • Culture of trust, empowerment and constructive feedback, meetups, game nights, knowledge sharing through tech talks, product demos, parties & events
  • Competitive salary, employee share shops, centrally located offices, public transport discounts, municipality services, great IT equipment, flexible working times, additional holidays and volunteering time off, free beverages and fruits, diverse sports and health offerings
  • Extensive onboarding, mentoring and personal development opportunities and an international team of experts 
  • Relocation assistance for internationals, PME family service and parent & child rooms* (*available in select locations)

About Customer Care Technology

The Customer Care Engineering Team builds statistical models, and one of the broad product areas driven by the team would be to anticipate and understand key dissatisfaction drivers in the customer journey and leverage these to define proactive communication strategies to minimize contacts and lead to frictionless experience.

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