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Data Scientist - Bayesian
Role Overview
Pythia Sports are looking for a creative thinking and experienced person to join their established in-house modelling team as a Data Scientist specialising in Bayesian modelling and simulation. The purpose of the role is to develop and conduct statistical analysis of predictive models for a horse racing prediction pipeline.
Most of Modelling team are currently working hybrid.
- Additional pay: Bonus scheme
- Schedule: Monday to Friday
- Education: PhD (preferred)
Benefits:
- 28 days + Bank Holidays leave
- Purchase up to 5 extra days of holiday/year
- Casual dress
- Company events
- Cycle to work scheme
- Flexible schedule
- Private medical insurance
- Optical and Dental cover
- Generous paternity and maternity leave
- Referral programme
- Company sick pay
- Work from home/office
Data Scientist - Bayesian
- Have a deep understanding of the data, its limitations and meaning, including the investigation of data validity
- Build and maintain Bayesian-driven predictive models
- Research and apply novel Bayesian modelling techniques
- Develop and maintain model validation metrics to regularly track and evaluate performance
- Understand and communicate the limitations and uncertainty of any model output
- Ensure the statistical robustness and validity of all models
Key Skills / Qualifications
- Experience utilising advanced Bayesian statistics and modelling techniques – preferably in a sporting context
- PhD or equivalent industry experience in data science, statistics, or a related field
- Proficiency in Bayesian inference techniques such as Markov Chain Monte Carlo (MCMC), Gibbs sampling, or variational inference
- Experience with Bayesian software packages (e.g., Stan, Turing.jl, PyMC3, JAGS)
- Ability to interpret and communicate probabilistic results to non-technical stakeholders
- Strong programming skills, with a preference for (but not limited to) Matlab, Python and R
- A long and proven track record of using data to solve complex problems
- Knowledge and interest in sports is beneficial
- Experience working with cloud computing (desirable).