Econometrician/Data Scientist

MBN Solutions
London
3 weeks ago
Applications closed

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Team Lead - Data Science

Econometrician / Data Scientist

Location: Central London (Hybrid)

£45,000-£50,000


MBN's client, an established and fast-growing marketing effectiveness agency on a mission to help brands truly understand what’s driving performance — and how to do better. Our work is grounded in rigorous analytics and trusted by some of the world’s most recognisable brands.

As demand for our services grows, particularly within the FMCG space, we’re looking for askilled Econometrician / Data Scientistwith hands-on experience inMarketing Mix Modelling (MMM)to join our team.


🔍 About the Role

You’ll take ownership of end-to-end modelling projects — from data ingestion through to modelling, validation, and producing client-ready outputs. While direct client interaction is limited in this role, your work will be at the core of delivering meaningful insights and commercial value.

You’ll work alongside a collaborative, ego-free team that values openness, technical rigour, and continuous improvement.


✅ What You’ll Be Doing

  • Lead MMM modelling projects: from data prep, exploration, and variable selection through to final model delivery
  • Build clear, insightful analysis decks for internal teams and client presentations
  • Apply econometric techniques including regression modelling, adstock, saturation, lag structures, and more
  • Continuously improve processes as part of a company that invests heavily in technical development


What We’re Looking For


Must-haves:

  • 2–3 years of hands-on MMM experience
  • Strong modelling skills in R, Python, or similar statistical tools
  • Confident handling, cleaning, and transforming large datasets
  • Analytical mindset with a sharp eye for detail
  • Ability to work independently on modelling tasks from start to finish

Nice-to-haves:

  • Familiarity with FMCG data and media mix variables (TV, digital, OOH, promotions, etc.)
  • Understanding of FMCG dynamics like seasonality, product cannibalisation, and baseline shifts

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