Design and develop valuation and forecasting models such as: Net Present Values, Customer Lifetime Value and Offer Economics to guide marketing budget optimization and investment decisions.
Apply advanced statistical and causal modeling to quantify incremental impact, uncertainty and trade-offs.
Analyze large datasets to understand customer behavior and translate insights into clear business cases with measurable outcomes.
Own the full analytical lifecycle, from problem framing and data exploration to model development and validation.
Partner with marketing strategy, finance, and data teams to drive adoption of valuation outputs, advise on their application, and present findings clearly to senior executives to support strategic decisions.

Advanced degree in a quantitative field (e.g., mathematics, statistics, economics etc.) is preferred.
Progressive experience in data science, advanced analytics, or quantitative modeling, preferably in financial services or marketing analytics.
Demonstrated expertise in marketing valuation concepts, including customer lifetime value, incremental or causal value and offer or channel economics.
Intermediate proficiency in Python and SQL.
Knowledge of cloud platforms and big data technologies (Spark, Hadoop).
Excellent communication skills with the ability to explain complex approaches to non-technical and executive stakeholders.
Strong attention to detail.

Senior Data Scientist – Marketing, Customer Analytics

Key skills