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