Senior Data Scientist: Bayesian Analytics & Production ML

WPP Media; København; Hybrid; DKK 700,000 - 980,000; Full time

Job summary

WPP in Denmark is expanding its data science capability to develop a state-of-the-art system for estimating audience sizes and characteristics. The role offers the opportunity to apply Bayesian statistics, advanced mathematical thinking and production-quality engineering to meaningful industry problems.

You’ll build production-ready Python packages, collaborate with data scientists and engineers, and ensure data quality across the analytics pipeline while leveraging cloud resources for scalable

Qualifications

• Advanced knowledge of probability and statistics, with Bayesian methods.
• Strong Python programming skills, including package development and unit testing.
• Experience translating complex mathematical questions into data-driven solutions.

Responsibilities

• Develop and implement Bayesian statistical models and other methods to estimate audience sizes.
• Translate complex questions into robust, explainable solutions.
• Build and maintain production-ready Python packages with tests and docs.
• Collaborate with data scientists, engineers and other specialists.
• Ensure data quality and integrity across the analytics pipeline.
• Leverage cloud resources for scalable data processing and deployment.
• Contribute to code reviews and version-control practices.

Skills

Bayesian statistics

Python

Data analysis

Git

Communication

Education

Postgraduate degree or equivalent experience

Tools

Git

AWS/GCP/Azure

Job description

WPP in Denmark is expanding its data science capability to develop a state-of-the-art system for estimating audience sizes and characteristics. The role offers the opportunity to apply Bayesian statistics, advanced mathematical thinking and production-quality engineering to meaningful industry problems.

You’ll build production-ready Python packages, collaborate with data scientists and engineers, and ensure data quality across the analytics pipeline while leveraging cloud resources for scalable