Data Scientist with PyMC & Marketing Mixed Modelling experience

Lorien; City Of London; Hybrid; GBP 100,000 - 125,000; Part time

Job summary

A leading recruitment agency is seeking a Data Scientist with experience in PyMC and Marketing Mixed Modelling for a 6-month contract in London. The successful candidate will work with the Data Science team to drive Marketing Effectiveness using advanced modelling techniques. Key responsibilities include overseeing data collection, building models, and validating results. A strong background in statistical modelling and proficiency in Python and SQL are required.

Qualifications

• Proven experience in developing Marketing Mix Models.
• Expert in PyMc and Python, familiar with R.
• In-depth understanding of statistical modelling techniques.

Responsibilities

• Oversee data collection including extraction and validation.
• Analyse datasets to understand KPIs for modelling.
• Build models according to project specifications.

Skills

Developing Marketing Mix Models

Expert in PyMc

Expert in Python

Statistical modelling/ML techniques

Data mining with SQL and Spark

Education

MS or PhD in Data Science or related field

Tools

Excel

SQL

Python

Pandas

Azure

Job description

Data Scientist with PyMC & Marketing Mixed Modelling experience

Job Type: Contract/Temporary

Location: London

Negotiable

Job Ref: BBBH160520_1762165166

Date Added: November 3rd, 2025

Consultant: Louis Poynter

Data Scientist with PyMc & Marketing Mixed Modelling experience
6 Months Contract
Inside IR35
Remote/1 day onsite a month
Bankside

My client a top Global company are currently looking to recruit a Data Scientist with PyMc & MMM experience to join their team on a 6-month contract basis. Please note if successful this position will need to set up via an Umbrella Company/PAYE. This Senior Data scientist required to work with our clients Data Science team to drive Marketing Effectiveness using Marketing Mix Modelling, Multi‑Touch Attribution, and other models.

Responsibilities

• Oversee and be responsible for data collection including data extraction and manipulation, data analysis and validation.
• Analyse all datasets to ensure that each KPI is understood, and data is ready for modelling.
• Proficiency in using Excel/SQL/Python/Pandas to process, transform, create variables, and build models.
• Build base models according to the project specification, incorporating all drivers of KPIs, providing rationale for variables selection, understanding coefficients and contributions.
• Taking base models, oversee or build in additional improvements and progress the model towards finalisation
• Create sales effect/ ROI workbook,
• Create response curves and optimisation charts
• Budget allocation. Run scenarios required to answer client objectives for the purpose of forward looking optimization,
• Validate models, identify areas of weakness, suggest and test possible improvements and ensure robustness and validity.

Requirements

• Proven experience in developing and implementing Marketing Mix Models
• Be an expert in PyMc, Python and familiar with R programming for MMM Models
• Have in depth understanding of statistical modelling / ML techniques
• Experience with Regression based models applied to the context of MMM modelling
• Solid experience with Probabilistic Programming and Bayesian Methods
• Be an expert in mining large & very complex data sets using SQL and Spark
• Have in depth understanding of statistical modelling techniques and their mathematical foundations,
• Have a good working knowledge of Pymc and cloud-based data science frameworks and toolkits. Working knowledge of Azure is preferred
• Have a deep knowledge of a sufficiently broad area of technical specialism (Optimisation, Applied Mathematics, Simulation)

MS or PhD degree in Data Science, Computer science, applied mathematics, statistics, or another relevant discipline with a foundation in modelling and computer science is highly desirable

Carbon60, Lorien & SRG - The Impellam Group STEM Portfolio are acting as an Employment Business in relation to this vacancy.