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# Senior Data Scientist - MMM

- **Company:** Harnham
- **Location:** London, UK (Remote available)
- **Experience:** Expert
- **Salary:** £70,000.0 - £90,000.0
- **Contract:** Permanent contract
- **Skills:** Cloud Computing, Data Infrastructure, Data Warehousing, Statistical Hypothesis Testing, Python (Programming Language), Regression Analysis, Sql Optimization
- **Published:** October 20, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/senior-data-scientist-mmm/52823238

## About the Role

Strong commercial experience in Marketing Mix Modelling, marketing measurement, or advanced marketing analytics.
Excellent understanding of experimentation, incrementality testing, and causal inference methodologies.
Strong statistical knowledge, including hypothesis testing, regression analysis, and experimental design.
Advanced SQL skills and experience working with Python for analytics and modelling.
Experience using modern data platforms and cloud-based analytics environments.
Ability to communicate technical findings effectively to non-technical stakeholders.
Comfortable working in a fast-paced environment with a high degree of ownership.

## Description

Senior Data Scientist, MarketingRemote (UK) | £70,000 - £90,000An exciting opportunity to join a fast-growing, data-driven business where marketing measurement sits at the heart of commercial decision-making. This role offers the chance to own advanced modelling initiatives, influence budget allocation, and shape how marketing performance is measured across the organisation.The CompanyThey are a digitally-focused consumer business operating at scale, with a strong commitment to data-led decision making. Their collaborative culture empowers employees to take ownership of high-impact projects and influence business strategy. With a modern data stack and a growing analytics function, they offer an environment where experimentation and innovation are actively encouraged.The Role
Own and develop the organisation's Marketing Mix Modelling (MMM) framework using modern modelling techniques.
Deliver actionable insights on marketing effectiveness, media performance, and budget allocation.
Design and evaluate incrementality testing programmes, including lift studies and geo-based experiments.
Partner with Marketing teams to improve attribution, measurement, and channel performance.
Build and maintain Lifetime Value (LTV) models to support acquisition and retention strategies.
Apply statistical and causal inference techniques to identify growth opportunities and optimise investment decisions.
Translate complex modelling outputs into clear recommendations for stakeholders.