8 of 8 Bayesian Methods Jobs in England

responsibilities: Own full MMM project cycles - from data strategy and modelling to insights, activation, and client recommendations. Apply econometrics, regression, Bayesian methods, and machine learning to large, complex datasets. Produce dashboards, decisioning tools, and visual analytics using internal frameworks. Translate technical outputs into clear, strategic recommendations … data science. Strong technical capability in Python, R, SQL; experience with cloud platforms (Azure, Databricks) beneficial. Solid grounding in econometrics, regression modelling, Bayesian approaches, or advanced statistical techniques. Proven experience turning analytical outputs into actionable commercial insights. Confident communicator with strong client-facing skills and the ability ...

responsibilities: Own full MMM project cycles - from data strategy and modelling to insights, activation, and client recommendations. Apply econometrics, regression, Bayesian methods, and machine learning to large, complex datasets. Produce dashboards, decisioning tools, and visual analytics using internal frameworks. Translate technical outputs into clear, strategic recommendations … data science. Strong technical capability in Python, R, SQL; experience with cloud platforms (Azure, Databricks) beneficial. Solid grounding in econometrics, regression modelling, Bayesian approaches, or advanced statistical techniques. Proven experience turning analytical outputs into actionable commercial insights. Confident communicator with strong client-facing skills and the ability ...

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 ...

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 ...

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 ...