National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Scientist (London)

Harnham
London
2 weeks ago
Create job alert

Job Opportunity: Marketing & Data Science - Measurement & Modelling


Location:Hybrid (2 days per week in office for first month, flexible after)
Duration:3 months initially
Rate:£450-480/day (Outside IR35)
Commute:2 hours by train from Central London

Role Overview:
This role focuses on marketing effectiveness and data science in the retail industry, with a strong emphasis on email campaign measurement, incremental value, and experimentation. The main responsibilities include finalising the Marketing Mix Modelling (MMM) framework, completing the A/B testing framework, and automating marketing analytics processes. The ideal candidate will have experience in causal inference, MMM, and experimentation.

Key Responsibilities:

  • Finalising the MMM framework and modelling (70% complete)

  • Building out the A/B testing framework

  • Automating marketing analytics processes, particularly around experimentation

  • Handling complex data and working with incomplete data

  • Measuring campaign impact and refining marketing strategies

Tech Stack:

  • Core: Databricks, SQL, Python, PySpark

  • Nice to Have: R, dashboarding tools

Ideal Candidate:

  • 4-5 years of commercial experience in data science, preferably in an eCommerce or marketing analytics environment

  • Proven experience in causal inference, MMM, and experimentation

  • Strong communication skills and the ability to explain data-driven insights

Interview Process:

  • Stage 1: Technical assessment

  • Stage 2: Knowledge-based interview

Desired Skills and Experience

Key Skills & Experience:

4-5 years in data science, with a focus on marketing analytics

Strong experience in Marketing Mix Modelling (MMM) and A/B testing

Expertise in causal inference, experimentation, and incrementality measurement

Proficient in Databricks, SQL, Python, and PySpark

Ability to handle incomplete and complex datasets

Experience with customer lifecycle modelling and LTV

Strong communication and ability to explain data-driven insights

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist role - Financial Services | Guildford £80k

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist (Marketing Mix Modelling/Python/Pymc) - £688 (Inside IR35) - London

Senior Data Scientist (London)

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.