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Marketing Mixed Modelling Data Scientist, London (City of London)
Client: Lorien
Location: London (City of London), United Kingdom
Job Category: Other
EU work permit required: Yes
Job Views: 2
Posted: 16.06.2025
Expiry Date: 31.07.2025
Job Description:
Data Scientist with PyMc & Marketing Mixed Modelling experience
6 Months Contract
Inside IR35
Remote/1 day onsite a month
My client, a top global company, is 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 be set up via an Umbrella Company/PAYE. This senior Data Scientist will work with our client's 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, manipulation, analysis, and validation.
* Analyze datasets to ensure KPIs are understood and data is ready for modelling.
* Proficiency in Excel, SQL, Python, Pandas for data processing, variable creation, and model building.
* Build base models according to project specifications, incorporating all drivers of KPIs, providing rationale for variable selection, understanding coefficients and contributions.
* Improve and finalize models by adding enhancements.
* Create sales effect/ROI workbooks, response curves, and optimization charts.
* Conduct scenario analysis for budget allocation and forward-looking optimization.
* Validate models, identify weaknesses, suggest improvements, and ensure robustness.
Requirements:
* Proven experience in developing and implementing Marketing Mix Models.
* Expertise in PyMc, Python, and familiarity with R programming for MMM models.
* Deep understanding of statistical modeling and ML techniques.
* Experience with regression-based models in MMM contexts.
* Solid experience with probabilistic programming and Bayesian methods.
* Expertise in mining large, complex datasets using SQL and Spark.
* Understanding of statistical modeling techniques and their mathematical foundations.
* Good working knowledge of PyMC, cloud-based data science frameworks, and Azure (preferred).
* Broad knowledge of technical specialisms like optimization, applied mathematics, or simulation.
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