Econometric Modelling Lead (Marketing Mix Modelling)

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Econometric Modelling Lead (Marketing Mix Modelling), slough

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Client:

DATAHEAD

Location:

slough, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

2

Posted:

31.05.2025

Expiry Date:

15.07.2025

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Job Description:

Own the insight. Lead the impact.

Join a multi-award-winning analytics powerhouse that’s redefining how brands measure success. We’re looking for a rising star in Marketing Mix Modelling – someone with proven hands-on experience, hungry to lead delivery, shape strategy, and challenge conventional thinking in media measurement.

This is your opportunity to step into a leadership role within a collaborative, data-obsessed team that works across a global network of data scientists, engineers, and media specialists.

What You’ll Be Doing

• Lead end-to-end delivery of econometric projects—from scoping to insight delivery.
• Be the face of MMM : Own client relationships, manage stakeholders, and confidently present recommendations.
• Build and refine automated, scalable modelling solutions using Python, R, or SQL.
• Collaborate with internal Centres of Excellence to push boundaries in analytics and attribution.
• Help shape innovative data science products that move the needle for clients.
• Mentor and inspire junior team members, fostering growth and excellence.

What You Bring

• Hands-on experience in MMM/econometric modelling.
• A strong grounding in statistical modelling with the ability to translate complexity into clarity .
• Confident storyteller—able to explain technical insights in commercial terms.
• Solid skills in Python, R, or SQL (or eager to level up).
• Experience with scenario planning and delivering high-impact outputs for marketing/media teams.
• Comfortable working within agency or consultancy environments.

Bonus Points For:

• Familiarity with cloud platforms like GCP/BigQuery or handling large datasets.
• Exposure to Bayesian methods or advanced non-linear modelling approaches.
• Experience with open-source or proprietary MMM tools (e.g. Robyn, Meridian ).
• Background in econometrics, statistics, applied mathematics, or a similar quantitative field.

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