Job title: Senior Data Scientist Location: Remote (Within Spain) Contract Type: Freelance/Contract We're looking for an experienced Data Scientist to audit, redesign and rebuild chargeback estimation and revenue forecasting models.
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You will work on production grade pipelines within a dbt on Databricks stack, alongside a business facing scenario tool that which stakeholders to model the impact of price changes on expected revenue Key Responsibilities Audit and redesign chargeback estimation and revenue forecasting models Deliver production-grade pipelines in dbt (Databricks) and Python Build scenario/what-if tools for non-technical stakeholders (price sensitivity, revenue planning, unit economics) Apply interpretable, parametric modelling approaches — closed-form equations, demand/price curves, elasticity models, cohort survival curves, GLMs, and additive decompositions Ensure every model parameter carries a clear business meaning explainable in plain language Reconcile model outputs against accounting figures and communicate uncertainty in business terms Required Experience 5–8 years of senior data science or analytics engineering experience End-to-end ownership of a forecasting or financial estimation model in production Strong bias toward parsimony: price elasticity, demand curves, cohort/LTV curves, survival models, GLMs preferred over black-box ML Stack: Python (pandas, numpy, scikit-learn, statsmodels, scipy.optimize), dbt (incremental models, tests, snapshots), Databricks (Py Spark, Delta, jobs), advanced SQL Domain: Demonstrated work on chargebacks, payment risk, refund/dispute xpzdshu modelling, revenue forecasting, LTV, cohort revenue projections, or pricing/elasticity Languages: Spanish C1+ (working day-to-day with finance/ops stakeholders) and English B2+ (documentation) Comfortable reconciling model outputs against accounting figures and explaining uncertainty in business terms Nice to Have Payments, fintech, subscription, or e-commerce background MLflow on Databricks, Unity Catalog, Databricks Workflows, or Airflow Prior consulting or fixed-scope engagement track record (references preferred)