Bayesian Data Scientist

JR United Kingdom; Slough; On-site; GBP 55,000 - 80,000; Full time

Job summary

A leading FMCG brand invites applications for a Bayesian Data Scientist to join their advanced Data Science team. This role focuses on enhancing marketing effectiveness through Bayesian Marketing Mix Modeling, requiring deep expertise in statistics and data-driven optimization strategies. Candidates should have expert Python skills and be adept at managing complex datasets, with an educational background in relevant quantitative fields.

Qualifications

• Extensive experience in building Marketing Mix Models focusing on Bayesian methods.
• Expert-level proficiency in Python with tools like pandas and NumPy.
• Strong ability to handle large datasets using SQL/Spark.

Responsibilities

• Lead data workflows: extraction, transformation, validation, and analysis.
• Build and refine Bayesian MMM models for marketing KPIs.
• Run simulations for strategic marketing decisions.

Skills

Bayesian methods

Python

Data analysis

Model validation

Statistical inference

Education

MSc or PhD in Statistics, Data Science, Applied Mathematics, or related field

Tools

SQL

R

Azure

pandas

NumPy

PyMC

Spark

Job description

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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 Bayesian Data Scientist 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.