Lead Econometrician in City of London

Lead Econometrician in City of London

City of London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Harnham

At a Glance

  • Tasks: Lead Marketing Mix Modelling and shape a growing data science team.
  • Company: Global media and analytics business focused on marketing performance.
  • Benefits: Competitive salary, high ownership, and clear career progression.
  • Other info: Join at an early stage and influence client outcomes and internal growth.
  • Why this job: Make a real impact by building a data science function from the ground up.
  • Qualifications: Experience in Marketing Mix Modelling and proficiency in Python.

The predicted salary is between 60000 - 80000 £ per year.

This is a high-impact leadership role offering the opportunity to build and scale a data science function in the UK. You will take ownership of Marketing Mix Modelling delivery while shaping the long-term vision of the team, combining hands-on technical work with senior stakeholder engagement. With strong investment in data capabilities, this role offers real influence over both client outcomes and internal growth.

The Company

They are an established global media and analytics business focused on understanding the true drivers of marketing performance and profitability. Built with a strong technical foundation, they bring together experimentation, proprietary tools, and data science to inform strategic marketing decisions. As part of a wider transformation, they are investing in building a UK-based data science team to bring capability closer to clients. This creates an opportunity to join at an early stage and play a central role in shaping how the function evolves.

The Role

  • Lead the end-to-end delivery of Marketing Mix Modelling using frameworks such as Meridian, Robyn, or PyMC
  • Oversee all stages of model development including data preparation, calibration, validation, and scenario planning
  • Translate complex statistical outputs into clear, commercially actionable insights for senior stakeholders
  • Act as the senior point of contact for clients, supporting both delivery and strategic discussions
  • Balance hands-on technical work with leadership responsibility, with scope to evolve as the team grows
  • Build and develop a high-performing data science team, setting standards and supporting capability growth
  • Contribute to business development, including supporting pitches and shaping the data science proposition

Your Skills and Experience

  • Strong commercial experience delivering Marketing Mix Modelling projects end-to-end
  • Proficiency in Python with experience using open-source MMM frameworks such as Meridian, Robyn, or PyMC
  • Solid grounding in statistical modelling, including Bayesian approaches and media attribution
  • Proven experience working in a client-facing environment, delivering insights to senior stakeholders
  • Experience leading or mentoring data scientists while remaining hands-on technically
  • Ability to assess model quality and translate outputs into clear business recommendations

What They Offer

  • Opportunity to build and shape a growing data science function
  • High level of ownership and visibility across the business
  • Clear progression as the team and capability expand

How to Apply

If you are interested in leading impactful data science work and building a function from the ground up, please get in touch to learn more.

Harnham

Contact Details:

Harnham Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead Econometrician in City of London

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We think you need these skills to ace Lead Econometrician in City of London

Marketing Mix Modelling
Data Preparation
Model Calibration
Model Validation
Scenario Planning
Statistical Modelling
Bayesian Approaches

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Brush Up on Your Statistics

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