11 of 11 Permanent Bayesian Methods Jobs in England

Doing Designing novel algorithmic and machine learning approaches to interpret complex scientific data Developing mathematical models (including probabilistic/Bayesian methods) Building proof-of-concept tools and production-ready Python systems Managing and improving data pipelines from experimental instrumentation Continuously evaluating, refining, and stress-testing models … depth. What They’re Looking For... Essential STEM degree (undergraduate or above) Strong Python software engineering skills Comfort working with mathematical modelling and statistical methods Intellectual curiosity and willingness to explore new approaches Nice to Have Experience in machine learning (research or applied) Probabilistic modelling or Bayesian ...

working with Marketing Mix Modelling (MMM) Strong statistical and econometric modelling expertise Hands-on experience with Python and data analysis workflows Exposure to Bayesian modelling approaches Experience with data visualisation tools (Plotly, Dash or similar) Familiarity with cloud environments (e.g. AWS) Curiosity and practical experience using ...

like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate ...

engineers • Some front-end/product sense (you care about shipping usable tools, not just notebooks) • Experience with causal inference, Bayesian methods, or mechanistic simulation ...

product, typically you'll collaborate with the research team to productionise ideas that are ahead of the published literature, evaluating and integrating established methods or developing your own algorithms, ensuring reliability and maintainability within a complex, integrated codebase. You'll liaise with clients to understand engineering problems that … when to ask for help from domain experts, researchers and engineers You have strong foundations in probabilistic modelling (Gaussian processes, Bayesian methods, uncertainty quantification) You're a confident communicator, comfortable liaising with clients What's in it for you: Competitive salary - to £90k Private Health Care ...

engineering—to translate business objectives into robust analytical solutions. Build software using modern technology to enable investing and asset management at scale. Apply Bayesian modelling and probabilistic programming techniques to address uncertainty and improve prediction accuracy. Analyse large-scale datasets to identify key drivers, trends, and early … Requirements: University degree in a STEM field (e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred. Strong expertise in statistical modelling, Bayesian inference, and machine learning. Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan) Experienced in SQL. Ability ...

firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung. Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts. Our 1,800 employees operate in 25 countries … client stakeholders. Advanced Modelling : Proven ability to implement a range of complex models such as time-series forecasting, gradient boosting, clustering, NLP, and Bayesian inference. ML-Ops & Orchestration : Strong experience with MLOps tools for orchestration, experiment tracking, hyper-parameter tuning, and deploying automated model retraining pipelines. Programming ...

Automation, Scripting & Visualization: Leveraging automated data processing, scripting, and interactive visualization to uncover insights, streamline workflows, and support sustainability goals. Design of Experiments & Bayesian Optimization: Implementing Bayesian and state-of-the-art approaches to maximize experiment efficiency and accelerate material and process development. Materials ...

Automation, Scripting & Visualization: Leveraging automated data processing, scripting, and interactive visualization to uncover insights, streamline workflows, and support sustainability goals. Design of Experiments & Bayesian Optimization: Implementing Bayesian and state-of-the-art approaches to maximize experiment efficiency and accelerate material and process development. Materials ...

market price prediction - you understand basis risk, seasonality, mean-reversion, and regime shifts intuitively You're fluent in multivariate modelling: VAR/VECM, Bayesian hierarchical models, factor models, LSTM/transformer-based temporal architectures - and you can speak clearly to the tradeoffs between them You're rigorous … model that moves a negotiation outcome is worth more than one that wins a Kaggle leaderboard Nice to Have Experience with causal inference methods applied to market dynamics (synthetic control, difference-in-differences, IV) Familiarity with procurement indices (PPI, ISM, commodity spot/futures markets) and how to incorporate ...

Researcher you will work fairly independently, developing your own research programme, with a view to developing new tools and techniques for probabilistic models, Bayesian optimisation and related fields. You will actively engage in team collaborations to meet research goals and report your research findings both internally and … advanced knowledge of decision making techniques e.g. Bayesian optimisation, bandits, reinforcement learning, active learning and/or probabilistic modelling and methods e.g. Gaussian processes, Bayesian neural networks, Variational inference, etc. You have experience with Python numerical programming e.g. NumPy, TensorFlow, PyTorch Ideally ...