Senior Econometrician

Datatech Analytics; City Of London; Hybride; GBP 45 000 - 55 000; Plein temps

Résumé du poste

Datatech Analytics in London is seeking a Senior Econometrician to lead Marketing Mix Modelling projects, combining hands-on modelling with interpretation and stakeholder engagement.

You will own the modelling lifecycle from data prep to final outputs, present findings to clients, and mentor junior colleagues, with a hybrid policy of 2–3 days in the office.

The role offers a London salary range £45k–£55k depending on experience and aims to strengthen the team's analytical capabilities.

Qualifications

• 3+ years in Marketing Mix Modelling (MMM).
• Strong econometric skills using R/Python or SAS.
• Experience cleaning and transforming large datasets.
• Understanding of linear and non-linear modelling approaches.
• Ability to translate outputs into business insights.

Responsabilités

• Manage the full MMM modelling lifecycle from data to delivery.
• Prepare and quality-check datasets for analysis.
• Apply econometric methods to assess marketing performance.
• Present findings and recommendations to stakeholders.
• Lead project delivery with limited supervision.
• Identify improvements to modelling processes.

Connaissances

Marketing Mix Modelling

Econometric modelling

Data interpretation

Stakeholder engagement

Independent project work

Outils

EViews

SAS

Pandas

Parquet

Description du poste

Senior Econometrician - Marketing Mix Modelling

London / Hybrid - 2-3 days per week in the office

Salary: £45,000 - £55,000 DoE

Ref: J13198

Our client is a growing specialist analytics consultancy helping consumer brands better understand the effectiveness of their marketing activity. Using advanced statistical modelling and data-driven analysis, they help businesses measure performance, optimise investment and identify opportunities for future growth.

With an increasing number of projects and continued investment in its analytical capabilities, the business is looking to bring an experienced Senior Econometrician into its team. This is an opportunity to join a technically focused environment where you'll have the autonomy to lead projects, contribute ideas and develop beyond the purely technical aspects of your role.

You’ll be involved throughout the project lifecycle, combining hands-on modelling with interpretation, presentation and stakeholder engagement. For someone looking to strengthen their project leadership skills and build a broader commercial understanding, there's plenty of scope to make an impact.

What you'll be doing

• Manage the full modelling lifecycle, including understanding project requirements, exploring datasets, selecting variables and developing appropriate models


• Prepare and quality-check data, ensuring datasets are accurate, consistent and suitable for analysis


• Apply appropriate econometric methodologies to investigate marketing performance and generate reliable results


• Use techniques such as regression, adstock, lag structures, saturation and interaction effects to strengthen model performance


• Evaluate models through validation, diagnostic testing and relevant performance measures


• Produce clear, engaging presentations that explain findings, implications and recommendations


• Translate complex statistical outputs into practical insights that support commercial decision-making


• Take ownership of project delivery, managing the journey from raw data through to completed outputs with limited day-to-day supervision


• Identify opportunities to improve analytical processes, modelling efficiency and the quality of deliverables


• Contribute to the development of new analytical approaches and service offerings


• Work with colleagues and clients to ensure outputs address the underlying business questions


• Share knowledge and provide practical support to less experienced team members

You’ll ideally have:

• At least 3 years' practical experience in Marketing Mix Modelling (MMM)


• Strong statistical and econometric modelling capabilities using R, Python or tools such as EViews or SAS


• Experience preparing, cleaning and transforming large or complex datasets


• A solid understanding of different modelling methodologies, including linear and logarithmic-linear approaches


• Practical knowledge of regression, adstock, lag structures, saturation and interaction effects


• Experience assessing model accuracy, performance and reliability through validation and diagnostic techniques


• Familiarity with Python data libraries such as Pandas; knowledge of Parquet is advantageous


• Exposure to machine learning approaches, particularly Random Forest, would be beneficial


• The ability to manage modelling assignments independently, from initial data preparation to final delivery


• Experience presenting analytical findings through structured reports and presentations


• Strong problem‑solving skills and the ability to apply analytical thinking to real business challenges


• Clear communication skills, with the ability to explain technical concepts to non‑technical audiences


• Confidence working with stakeholders and some experience contributing to client discussions


• An interest in supporting junior colleagues and helping develop the wider team's capabilities

Candidates must have the right to work in the UK without sponsorship requirements.