1 to 25 of 31 Remote/Hybrid Bayesian Methods Jobs in the UK

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 ...

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 ...

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 ...

with strong foundations, deep structured‐data experience, and the judgement to apply the right level of complexity – from simple, robust baselines to more advanced methods where they add clear value. Key Responsibilities What will you be doing? Our direction of travel includes: Early-warning and lifecycle modelling. For rent … Time Time‐to‐event and state‐transition approaches (e.g. discrete‐time classification, roll‐rate models) for lifecycle and hazard problems. Forecasting using classical statistical methods, Bayesian/state‐space approaches, and modern pretrained time‐series foundation models. Connecting Models to Real Decisions Framing problems like contact ...

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 ...

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 ...

technical leadership: mentoring, setting standards, and influencing scientific and technical direction beyond your own projects. Beneficial Skills Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real‐world loops. Familiarity with retrosynthesis ML, computer‐aided synthesis planning (CASP), or reaction‐condition/ ...

Analyst or Data Scientist Minimum 2:1 in a Quantitative subject ideally Masters Experience OR an interest in Modelling – CHAID, Cluster Analysis, Bayesian Algorithms, NN, Experience with visualisation tools would be nice Python and SQL experience ideally - Python a MUST Experience in a Data Science role with ...

years line management responsibilities.Hands-on experience in population PK/PD, disease progression modeling, and clinical trial simulations.Strong understanding and knowledge of Bayesian methodologies, model-based meta-analyses, PBPK, QSP, and AI/ML in Pharmacometrics.Expertise in R, NONMEM or related pharmacometrics software.Are you ready ...

shipping ML productsPhD or other experience in a research environmentDeep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clusteringStrong stats or math backgroundVisualization, data skills, SQL, matplotlib, etc.Benefits We are a well treated bunch, with awesome benefits! If there ...

international clients, from data strategy and collection to modelling, insights, and activation.· Apply econometrics, regression, Bayesian statistics, and machine learning methods to analyse marketing and customer data· Collaborate closely with Managers to understand the project scope, structure, analytical approaches, manage operations and ensure timely delivery.· Build … similar tools.· Experience with Databricks, Azure, or other cloud/data platforms is a plus.· Solid understanding of econometrics, regression analysis, Bayesian statistics, or other advanced modelling techniques.· Experience translating data and model outputs into actionable business recommendations.· Comfortable handling large datasets, optimizing data pipelines, and delivering ...

products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Benefits Competitive salary and equity in a fast‐growing start‐up We serve lunch every weekday ...

shipping ML productsPhD or other experience in a research environmentDeep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clusteringStrong stats or math backgroundVisualization, data skills, SQL, matplotlib, etc.Benefits We are a well treated bunch, with awesome benefits! If there ...

products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Benefits Competitive salary and equity in a fast-growing start-up We serve lunch every weekday ...

rich environments Strong statistical knowledge Experience with product analytics and behavioural tracking Experience mentoring or coaching other analysts Nice to have Knowledge of Bayesian or Frequentist experimentation approaches Experience with event-level analytics platforms Predictive analytics exposure The team You'll report into the Analytics Team Lead ...

Make your mark for patientsWe are looking for a Principal Computational Methodologist who is curious, collaborative, and impact-driven to join our Advanced Methods and Data Science team within Biometrics and Data Science, based in any of our Brussels (Belgium), Slough (UK) or Raleigh (US).About the roleYou will … help shape how advanced AI, machine learning, and computational methods support clinical development. You will design, validate, and deploy models that help teams make evidence-based decisions in areas such as biomarker discovery, clinical trial design, operational efficiency, and patient experience. You will guide scientific thinking, turn complex methods ...

algorithms, tuning, and performance evaluation. Experience with a range of feature engineering techniques (e.g., target encoding). Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation. Experience in writing clean, production‐grade Python code for both model training and inference. Excited to leverage LLMs ...

supervised ML algorithms, tuning, and performance evaluation.Experience with a range of feature engineering techniques (e.g. target encoding).Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation.Experience in writing clean, production-grade Python code for both model training and inference.Excited to leverage LLMs for coding ...

work with product and engineering priorities. Nice to have Experience quantifying uncertainty in large models — calibration and confidence estimation via Bayesian methods, ensembling, steering, or prompt-based approaches. Experience with machine translation, multilingual NLP, or document-/layout-aware modelling experience. Familiarity with MoE-specific training ...

align research work with product and engineering priorities.Nice to haveExperience quantifying uncertainty in large models — calibration and confidence estimation via Bayesian methods, ensembling, steering, or prompt-based approaches.Experience with machine translation, multilingual NLP, or document-/layout-aware modelling experience.Familiarity with MoE-specific training and adaptation ...

qualified accounts that predict renewal, churn and expansion, in partnership with our GTM analytics.Establish a fit-for-scale experimentation and causal-inference approach. Pragmatic methods suited to our sample sizes (Bayesian readouts, holdouts, pre/post and quasi-experiments, guardrail metrics), and the judgement to know ...