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Satori Analytics is a fast-growing scale-up of 100+ tech specialists delivering innovative data and AI solutions across industries including FMCG, retail, manufacturing, and financial services. The company operates cloud-based ecosystems covering the entire data lifecycle from ingestion to AI applications, serving leading global brands across South-Eastern Europe and beyond.
You will join the Data Science team as a Senior Data Scientist focused on marketing science and marketing effectiveness. Your primary responsibility is developing and enhancing Marketing Mix Models (MMMs) to estimate the impact of media, promotions, pricing, seasonality, and other business drivers on organizational performance.
Key responsibilities include: building and refining MMMs using regression, time-series, econometric, and machine learning techniques to measure incremental impact while accounting for carryover effects, saturation, diminishing returns, and response curves; developing scenario-planning and optimization approaches to guide media budget allocation and investment decisions; evaluating model assumptions and business plausibility using SHAP, diagnostics, and sensitivity analysis; translating analytical outputs into clear recommendations on channel performance, ROI, and budget strategy for technical and non-technical audiences; partnering with Marketing, Commercial, Finance, BI, and Data Engineering teams to define KPIs and operationalize reproducible workflows; and supporting less-experienced colleagues in developing reusable methodologies and best practices.
Required qualifications include strong professional experience in Data Science, Marketing Science, Econometrics, or Commercial Analytics with demonstrated delivery of end-to-end modeling projects with business impact. You should have hands-on experience in Marketing Mix Modeling, sales/demand forecasting, pricing and promotions analytics, econometric or time-series modeling, or budget optimization. Strong statistical foundation is essential: regression, statistical inference, hypothesis testing, feature engineering, and model validation with comfort handling trends, seasonality, and lagged effects. Proficiency in Python or R and SQL (joins, CTEs, window functions) with libraries such as pandas, NumPy, scikit-learn, statsmodels, SciPy, and SHAP is required. You must be fluent in commercial concepts (ROI, ROAS, incremental revenue, margin, market share) and comfortable partnering directly with business teams. Ability to independently structure analytical workstreams, manage priorities, and communicate with senior stakeholders is essential. Git or version-control experience required.
Bonus qualifications include direct MMM building experience and familiarity with adstock, saturation, response curves, and baseline decomposition; constrained mathematical optimization tools (SciPy Optimize, CVXPY, Pyomo) and MMM frameworks (Google Meridian, Meta Robyn, LightweightMMM); causal inference, experiment design, geo-experiments, or incrementality testing; cloud platforms (Azure, AWS, GCP, Databricks, Microsoft Fabric, Snowflake) and MLOps exposure; and Generative AI or AI-assisted analytical workflow experience.
The role offers a hybrid work model with the option to work from the Athens office or remotely from anywhere in the European Economic Area, UK, or Switzerland (up to 6 weeks per year). Benefits include competitive salary, training budget for certifications and courses from top tech partners (Microsoft, AWS, Salesforce, Databricks), private insurance, and top-tier tech equipment.
