One of the most successful FinTech companies is looking for a skilled Senior Data Scientist with a focus on Marketing Automatization. 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 FinTech Data Experts, this is your chance.
A fun and driven atmosphere office in the heart of Stockholm.
A great diverse team of more than 100 data people including 10 Data Scientists.
Central Office in Berlin.
Flexible working hours.
Company incentives like a summer party, after work activity, fruits, snacks, coffee and drinks.
An interesting, challenging and varied job with a high degree of personal responsibility.
Further training opportunities.
30 days of paid holiday plus 24th and 31st of December paid holiday.
Improve the performance of current customer churn models, with the aim of reducing churn.
Build Customer lifetime value models, that helps identify the customers most valuable to the company.
Bring ideas to production using AWS.
Be involved in the whole process of model development. This includes everything from root cause analysis, data collection and feature engineering to training, validating and implementing machine learning models, computing performance statistics and live model monitoring.
Work closely with several engineering teams and business analysts to find new and smart ways of consolidating data and making use of it in order to make better models and ultimately better predictions.
Be part of the Engineering organization. Hence your workflow will be software-driven in terms of deploying models to production, using version control, and in general employing software engineering best practices.
A degree from a university in a highly technically numerate subject (e.g. Maths, Physics, Engineering or Economics).
Strong programming skills in Python, SQL and experience with popular machine/deep learning packages (e.g. scikit-learn, keras, tensorflow, mxnet)
Experience with & knowledge of: Cloud platforms such as AWS or Google Cloud; Big data using Hive, Spark, EMR
The theoretical foundations of classical and recent machine learning models and algorithms, such as generalized linear models, random forests and ensemble methods, deep neural networks etc.
Innovative, cooperative, collaborative, open and a flexible mindset with critical thinking.
If you are interested in discussing this role please apply with your current CV. Even if you are not actively looking at this time but are interested in other opportunities we may have, please reach out to Eva Sassnick.