1 to 25 of 64 Bayesian Methods Jobs in England

programs.Translate business questions into analytical problems and build solutions using visualization techniques, dashboards, machine and deep learning, and statistical modelling.Search and develop new algorithms, methods, statistical models and business models, providing insight into structured and unstructured data.Apply R-based analytical and statistical techniques to solve business problemsApplying data cleaning … science, biostatistics, or other quantitative field (or equivalent).Experience in clinical drug development with extensive exposure to clinical trials.Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods ...

Science, Economics, Engineering etc.)Knowledge of advanced statistical concepts and techniques, e.g. skilled in linear algebra.Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies. Proficiency ...

related to consumer behaviour, market trends, and campaign performance. - Build, maintain, and apply statistical and predictive models, including regression, econometrics, Bayesian methods, and Marketing Mix Modelling (MMM). -Develop dashboards, charts, and- visualizations to communicate insights effectively to clients and internal teams. - Assist in developing marketing ...

least 3 data or ML products from problem definition to production deployment and monitoring.Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale.Proficiency in SQL, Python, and familiarity with big data technologies (e.g. ...

build datasets suited for modelling and in-depth analysis.Design and execute measurement frameworks — including A/B testing, causal impact analysis, and multivariate methods — selecting the appropriate technique based on the business question and clearly communicating trade-offs.Build, evaluate, and iterate on statistical models (e.g. regression, clustering, classification), correctly … pricing, marketplace analytics, or a related domainFamiliarity with big data querying tools such as Presto, Hive, BigQuery, or HadoopExposure to Bayesian methods, causal inference, or multi-armed bandit approachesExperience collaborating with Machine Learning Data Science teams to validate and scale models for business impactFamiliarity with inclusive ...

build datasets suited for modelling and in-depth analysis. Design and execute measurement frameworks — including A/B testing, causal impact analysis, and multivariate methods — selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models (e.g. regression, clustering … analytics, or a related domain Familiarity with big data querying tools such as Presto, Hive, BigQuery, or Hadoop Exposure to Bayesian methods, causal inference, or multi-armed bandit approaches Experience collaborating with Machine Learning Data Science teams to validate and scale models for business impact Familiarity ...

build datasets suited for modelling and in-depth analysis. Design and execute measurement frameworks — including A/B testing, causal impact analysis, and multivariate methods — selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models (e.g. regression, clustering … analytics, or a related domain Familiarity with big data querying tools such as Presto, Hive, BigQuery, or Hadoop Exposure to Bayesian methods, causal inference, or multi-armed bandit approaches Experience collaborating with Machine Learning Data Science teams to validate and scale models for business impact Familiarity ...

cases as well as models.Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system performance ...

cases as well as models. Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Strong understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Skilled in handling large datasets, optimising pipelines, and delivering high-quality outputs Track record of translating complex model results ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus.· Strong understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques.· Skilled in handling large datasets, optimising pipelines, and delivering high-quality outputs· Track record of translating complex model results ...

deep learning, neural networks, reinforcement learning, and transfer learning.Familiarity with traditional machine learning algorithms such as random forests, SVM, logistic regression, and Bayesian modelling for model building, validation, and testing.Familiarity with cloud platforms (e.g., Bedrock, AWS, Azure) for model deployment and the creation of production-ready pipelines.Proficiency ...

intellectually curious, analytical, and passionate about understanding cause-and-effect relationships in complex systems. You bring strong quantitative skills and enjoy applying rigorous methods to high-impact business challenges.Experience applying causal inference techniques in a commercial, product, marketing, or research environment.Strong understanding of causal inference methods. Exposure to experimental … such as Double Machine Learning, Causal Forests, Meta-Learners, and Uplift Models.Experience evaluating incrementality, or uplift using experimental data.Knowledge of Bayesian methods for causal analysis and decision-making.Experience in gaming, e-commerce, or subscription-based products.Experience working with large-scale data using PySpark or equivalent distributed ...

fundamentals· Advanced data skills: statistical modelling, machine learning, time-series forecasting, demand prediction, optimisation, inventory management· Experience with dynamic pricing, stochastic processes, or Bayesian inference is a plusPreferred Experience:· Background in pricing, forecasting or optimisation roles within airlines, hospitality, car rentals, e-commerce, or similar dynamic pricing ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Deep understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Proven ability to handle large datasets, optimise pipelines, and deliver high-quality outputs. Track record of translating complex model ...

Python, SQL, Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus.Deep understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques.Proven ability to handle large datasets, optimise pipelines, and deliver high-quality outputs.Track record of translating complex model outputs ...

and non-technical stakeholders. Collaborative mindset and ability to work across data science, engineering, and business teams. Desirable Ability to build and evaluate Bayesian models using PyMC or Stan, with a focus on real-world forecasting applications. Formal work experience not required. Experience in pricing analytics, demand ...

view on where it helps and where it doesn't.The requirementsEssential:Statistical foundations. Strong grounding in probability and statistics, with an understanding of Bayesian reasoning and experience applying hierarchical modelling or decision-making under uncertainty.Causal inference. Experience separating signal from noise in observational and experimental data.Business translation. ...

experimental data, and in your penultimate year of study. Experience working with datasets using Python, R, SAS, MATLAB, or other statistical software. Experience with methods of statistical data analysis (e.g., linear models, hypothesis testing, multi-level models, Bayesian methods, etc.). Preferred qualifications: Experience with … search techniques. Produce quantitative and qualitative modeling of business dynamics, user behavior, and more. Identify areas for further investigation as well as creating innovative methods of analysis. Please complete your application before 23rd October 2026. We encourage you to apply as early as possible as we review applications ...

production.Track record of promoting statistical rigour and experimental best practices in your prior roles.Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)Experience working in a fast ...

and Bain’s wider technology platform.Define and maintain API contracts, agent and skill registry contributions, and shared user interface components.Support Artemis integrations with Bayesian marketing mix modelling capabilities and campaign performance data pipelines.Partner with AI Engineers to design large language model orchestration and tool-calling architectures ...

calculations, choosing the right unit of randomisation, guardrail metrics, interpreting inconclusive results.You have a proficient understanding of statistics — sample size, variance, multiple-comparisons, Bayesian reasoning.You know how to measure the incremental impact of ML models and CRM interventions end-to-end — defining success and guardrail metrics, designing ...

Stats Background • Outstanding background in probability and statistics • Experience and interest in modern machine learning techniques, for example, deep learning, Bayesian methods and graphical models • Programming experience with python, julia or R You will be joining a progressive and exciting company committed to excellence. They offer ...

model versioning, monitoring, automated retrainingUnderstanding of data engineering fundamentals and cloud platformsNice to haveHands-on experience building Marketing Mix Models end to end, Bayesian or regression basedBackground in consumer tech, mobile apps, or health techKnowledge of privacy-preserving ML techniques and A/B testing methodologyHow ...

through to multinationals, helping them secure highly sought after skill sets. Key words: Data Scientist, Algorithm Developer, Equity Research, Investments, Quantitative Research, Bayesian Statistics, Mathematics, Computer Science, Analytical Algorithms, Python. C++, Monte Carlo. ...