One of the most successful FinTech companies in Berlin is looking for a skilled Principal Data Scientist with focus credit risk and fraud detection. If you like to work in a driven, fun and ambitious work atmosphere, have the option to work from home whenever you want and learn from the most skilled Data Scientists and Machine Learning Engineers, this is your chance.

Benefits:

• A fun and driven atmosphere office in the heart of Berlin.
• A great diverse team of more than 100 data people including 10 Data Scientists.
• Flexible working hours.
• Company incentives like a summer party, afterwork activity, fruits, snacks, coffee and drinks.
• An interesting, challenging and varied job with a high degree of personal responsibility.
• Further training opportunities.
• Salary up to 90.000 ???.

Main Responsibilities:

• You are involved in the whole process of development, from analyzing the current status, data collection, cleaning, training, implementing machine learning features and performance monitoring.
• You work with AWS, Python, SQL, Hive and Spark to bring the machine learning models into production.
• You are the interface between several software development departments, data analysts and the business.
• You continuously increase automation and optimization with your own ideas and new input.

Your Profile:

• Bachelor degree or Masters in Computer Science or related technical fields.
• Minimum of 4 years of work experience in data science.
• Minimum of 2 years of work experience in credit risk and/or fraud detection.
• Fluent in Python and SQL including machine and deep learning libraries.
• Experience with AWS or GCP.
• Experience with Hive or Spark.
• Ideally, you have some knowledge about the state of the art technologies regarding machine learnig.
• Fluent in English, ideally fluency in one additional language.

If you are interested in discussing this role in a little more detail click apply. Even if you are not actively looking at this time but interested in other opportunities we may have, please reach out to Eva Sassnick.