Data Scientist for Buying and Churn

We need a data scientist to predict customer buying behavior and churn, measure which offers are most effective, and help set smarter discount strategies. The work includes building models, analyzing customer data, and turning insights into clear recommendations. You should be able to explain complex results in plain language and support decisions that improve customer retention and offer performance. This is a part-time role for someone who can work independently and deliver practical, data-driven solutions. Skills expected: Statistics and experiment design: you measure whether an offer or change really worked, including with moderate volume (for example uplift tests, holdout groups, Bayesian methods). Predictive models: purchase likelihood, repeat buying and churn, built and explained simply (for example Python with scikit-learn, XGBoost or LightGBM). Uplift modelling: you find who changes their behaviour because of an offer, not just who buys. Customer value prediction: you estimate what a customer will be worth over time. Customer groups: grouping customers by behaviour so each group can get its own message or offer. Pricing and discount analysis: you help set discount depth to protect margin.