Senior Data Scientist (Bayesian Modelling)
The Challenge Our client powers advertising measurement for some of the biggest brands in the US. They are completely rebuilding their flagship products around Bayesian frameworks, moving away from legacy frequentist methods to process tens of millions of data points with higher accuracy and speed. If you are considering sending an application, make sure to hit the apply button below after reading through the entire description.
They need a Senior Data Scientist to set the technical standard for Bayesian methods across a growing 25-person UK team. You will directly own core models, choose the best methods for the job, and see your work guide major commercial decisions. Drive Model Strategy: Select and build the right Bayesian, frequentist, or ML methods to continuously improve flagship measurement platforms.
Build Core Architectures: Construct hierarchical, time series, and audience models in PyMC, Stan, or NumPyro.
Set Technical Standards: Define team best practices for priors, diagnostics, posterior checks, and scalable inference.
Lead & Mentor: Guide junior and mid-level data scientists through code reviews, technical sessions, and shared best practices.
Commercial Translation: Communicate probabilistic outputs into clear, actionable business insights for client stakeholders. Bayesian Expertise: Practical experience with hierarchical models, MCMC, variational methods, and hands-on work in PyMC, Stan, or NumPyro.
Technical Stack: Strong proficiency in Python, SQL, and pandas (Polars or AWS experience is a plus).
Track Record: 5+ years of data science experience (PhD and postdoc work count toward this total).
Communication Skills: Ability to bridge the gap between complex probabilistic modeling and commercial decision-making. xehkeey Email Alaric at to receive the full job description and arrange an initial chat.
They need a Senior Data Scientist to set the technical standard for Bayesian methods across a growing 25-person UK team. You will directly own core models, choose the best methods for the job, and see your work guide major commercial decisions. Drive Model Strategy: Select and build the right Bayesian, frequentist, or ML methods to continuously improve flagship measurement platforms.
Build Core Architectures: Construct hierarchical, time series, and audience models in PyMC, Stan, or NumPyro.
Set Technical Standards: Define team best practices for priors, diagnostics, posterior checks, and scalable inference.
Lead & Mentor: Guide junior and mid-level data scientists through code reviews, technical sessions, and shared best practices.
Commercial Translation: Communicate probabilistic outputs into clear, actionable business insights for client stakeholders. Bayesian Expertise: Practical experience with hierarchical models, MCMC, variational methods, and hands-on work in PyMC, Stan, or NumPyro.
Technical Stack: Strong proficiency in Python, SQL, and pandas (Polars or AWS experience is a plus).
Track Record: 5+ years of data science experience (PhD and postdoc work count toward this total).
Communication Skills: Ability to bridge the gap between complex probabilistic modeling and commercial decision-making. xehkeey Email Alaric at to receive the full job description and arrange an initial chat.