Senior Data Scientist, Marketing
vor 1 Woche
**Some examples of real life projects we work on**:
- Build models for marketing channels impact decomposition (MMM) and further budget optimization for all business lines across 40+ countries together with our Data Analytics team and Marketing Science teams from Meta and Google.
- Predict best-next-action for our users for better marketing targeting.
- Predict customer lifetime value across business verticals for downstream use cases such as segmentation, budget optimization.
- Uplift modeling on user level that helps to distinguish profitable users from unprofitable ones
- Please note that _**_Berlin_**_ is a tech-hub where we are hiring locally only, and Bolt will not support your relocation to _**_Berlin_**_. However, relocation to Tallinn (our HQ) will be supported. See the relocation support we are providing_ here_.If this role is interesting to you, and you're currently located outside of _**_Berlin_**_, please consider this role in Tallinn, Estonia instead._
**Your daily adventures will include**:
- Building and maintaining machine learning & statistical models for forecasting, segmentation and optimization
- Utilizing causal inference to evaluate impact of marketing activities to drive acquisition, retention and engagement
- Optimize marketing spend allocation across different channels and campaigns to maximize ROI
- Support in building analysis frameworks for complicated cases of A/B testing and statistical analysis
- Collaborating with data analysts, data scientists, product managers, and software engineers in feature teams
- Working with a technical stack consisting of Python, Docker, SageMaker, Airflow, Presto, Spark
**We are looking for**:
***:
***:
- Industry experience in machine learning and data analytics (3+ years recommended)
- Knowledge of causal inference, statistics, probability
- Understanding experimental design such as A/B testing, quasi-experiments to evaluate interventions
- Strong product thinking, ability to communicate and persuade, problem solving
- Ability to map business and product problems on data science framework
- Effective communication and problem solving
- Familiarity with customer segmentation methods (RFM, LTV, similar audience models)
- Proactive mindset, willingness to take initiative and work with little supervision
- Team player with excellent communication skills
- Experience writing complex SQL queries
- Track record of deploying models to production and measuring the impact
**You will get extra credits for**:
- Experience in building large-scale Marketing Mix Modeling solutions, causal inference models & frameworks, multi-armed bandits
- Ph.D. in Computer Science, statistics or related quantitative fields, or a Master's degree with equivalent industry experience
- Background in econometrics, operations research, simulation or quantitative analysis of user behavior
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