Marketing Data Scientist / Econometrician

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.