Marketing Data Scientist / Econometrician
Location: London (Hybrid Working)
Contract Type: Initial 12 month contract + potential to extend long-term due to 3/4 year project scope.
Start Date: ASAP
We have an excellent opportunity for a Marketing Data Scientist / Econometrician to join a leading FMCG Brand, Initial 12 month contract + opportunity to extend long-term.
This is an exciting opportunity to join a high-performing Data Science team focused on advancing marketing effectiveness through advanced econometric modelling—including Bayesian Marketing Mix Modelling (MMM), Multi-Touch Attribution (MTA), and data-driven optimization strategies.
Key Responsibilities
* Lead and manage data workflows: data extraction, transformation, validation, and exploratory analysis to ensure modelling-readiness.
* Build and refine Bayesian MMM models that capture the drivers of key marketing and commercial KPIs.
* Use Python (and optionally R) to design, build, and improve base and advanced models—integrating prior knowledge, probabilistic reasoning, and real-world constraints.
* Develop and present ROI workbooks, response curves, and optimization frameworks for marketing budget allocation.
* Run scenario-based simulations to support strategic planning and forward-looking marketing investment decisions.
* Validate and stress-test models, identifying opportunities for improvement and ensuring robustness, interpretability, and business relevance.
Requirements
* Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods.
* Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC.
* Experience with R is a bonus, particularly for MMM-related workflows.
* Deep understanding of regression modelling, Bayesian inference, hierarchical models, and MCMC techniques.
* Proven ability to handle and analyse large, complex datasets using SQL and/or Spark.
* Solid knowledge of applied statistics, modelling techniques, and the mathematical underpinnings of inference and simulation.
* Familiarity with cloud platforms (Azure preferred) and modern data science toolkits.
* Advanced degree (MSc or PhD) in Statistics, Data Science, Applied Mathematics, Computer Science, or a related quantitative field.
Preferred Attributes
* Strong foundation in optimization, simulation modelling, and decision analytics.
* Demonstrated ability to translate complex Bayesian models into strategic insights and practical business outcomes.
* Strong communication skills and the ability to collaborate across marketing, analytics, and commercial teams.