26 to 50 of 62 Bayesian Methods Jobs in England

similar. ● PhD in Statistics or another area involving lots of work with messy data (e.g., Physics, Computational Biology). ● Extensive background in Bayesian inference, state-space models, filtering algorithms, etc. ● Excellent programming skills and experience implementing efficient algorithms for high-dimensional problems. Any prior exposure to sports ...

Engineering degree. Outstanding background in probability and statisticsExperience and interest in modern machine learning techniques, for example, deep learning, Bayesian methods and graphical modelsProgramming experience with python, julia or RYou will be joining a progressive and exciting company committed to excellence. They offer an excellent working ...

data pipelines using dbt, Airflow, and Snowflake. Beyond querying, you use Python for advanced automation and forecasting, and you apply statistical rigor (e.g., Bayesian statistics, causal inference) to solve complex product problems. Commercial & Risk Mindset: You possess deep commercial fluency, understanding the unit economics of a fintech ...

into a compelling product vision and strategic roadmap. Deep expertise in advanced measurement techniques including Marketing Mix Modeling (MMM) (including various methodologies like Bayesian), Multi-Touch Attribution (MTA), Incrementality testing, and marketing experimentation. Strong understanding of marketing data sources, data ingestion, transformation, and reporting challenges. Deep expertise ...

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 ...

Tools: C++, Python, Git, Docker, CI/CD, Linux, Docker/Podman ML specific skills Stochastic processes: behavior trees, FSMs, MDPs Learning: RL, Bayesian networks (and BBP) Scripting languages: PDDL, RDDL Nice to Haves Experience with SLAM, computer vision applied to UAVs Knowledge of AI safety principles ...

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 ...

teams to design and implement new statistical and machine learning features across Optimizely’s product suite. Conduct rigorous testing and validation of new statistical methods and ensure seamless integration into the platform. Analyze product performance data to optimize existing features and provide actionable recommendations for improvement. Leverage AI agents … deploy new statistical capabilities. Research and Innovation Partner with academic and industry researchers to explore cutting-edge statistical methods and machine learning innovations. Identify emerging trends in experimentation and statistics that could enhance Optimizely’s offerings. Propose and prototype advanced statistical techniques to solve challenging business problems faced ...

shaping a modern, cloud-native stack from an early stage. As an experienced technical leader and researcher, you'll use advanced predictive and prescriptive methods (causal inference, stochastic simulation, Bayesian hierarchical modelling, machine learning and more) to tackle real strategic and operational questions, e.g., forecasting …/equivalent experience in Data/analytics field Evidence of post qualifying and continuing professional development Demonstrable knowledge in relevant analytical fields, their associated methods, and their potential for application within healthcare, including advanced statistics, epidemiology, data science, econometrics, and operational research Expert knowledge of the role of analysis ...

duties and responsibilities will include, but won't be limited to building and improving sports prediction modelsTo research recent advances in Bayesian updating to better extract signals from noisy dataTo design and build your own models using your own ideasTo work closely with expert traders and developers ...

replacement for clinical and statistical expertise, but as a powerful complement to it. We hold ourselves to measurable standards of improvement, and we build methods that can be evaluated, reproduced, and trusted in regulatory settings. You will work across the enterprise to define and deliver on AstraZeneca's most … development questions — leading cross-functional teamsspanning the keyBioPharmaceuticalsdisease areas of cardiovascular, renal, metabolic disease, respiratory,immunologyand cell-therapy.You and the team will develop reusable methods and enterprise-scale approaches that measurably advance the late-stage drug pipeline. This is a high-visibility opportunity to shape how AstraZeneca does ...

replacement for clinical and statistical expertise, but as a powerful complement to it. We hold ourselves to measurable standards of improvement, and we build methods that can be evaluated, reproduced, and trusted in regulatory settings. You will work across the enterprise to define and deliver on AstraZeneca's most … teams spanning the key BioPharmaceuticals disease areas of cardiovascular, renal, metabolic disease, respiratory, immunology and cell-therapy. You and the team will develop reusable methods and enterprise-scale approaches that measurably advance the late-stage drug pipeline. This is a high-visibility opportunity to shape how AstraZeneca does ...

computer science, or equivalent experience with experience in research Proven experience applying machine learning techniques to solve business problems Proven experience in translating technical methods to non-technical stakeholders Strong programming experience in Python and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/…/keras, langchain). R and C++ optional. Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision Ability to write production code and object-oriented ...

senior specialist role focused on understanding the drivers of demand, outcomes, variation, inequalities and cost across our population. You will apply advanced analytical methods to complex system questions and translate findings into clear intelligence that supports senior decision making. The role will work closely with colleagues across analytics … generation and evaluation rather than routine reporting or dashboard development. Main duties of the job You will lead complex analytical and evaluative projects, applying methods such as regression, forecasting, segmentation, risk stratification, causal inference, impact evaluation, cost-effectiveness analysis and statistical modelling where appropriate. You will be experienced ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

bookmaker) Experience with and/or knowledge of Bayesian models, state space models, filtering and smoothing, computational statistics and approximate inference methods Experience with and/or knowledge of machine and statistical learning, deep neural networks, feature engineering, reinforcement learning, dynamic optimisation and optimal control Experience ...

analyses, develop protocols, and provide senior statistical leadership across multiple engagements with clients. The role requires hands-on expertise in Bayesian methods, ITCs, survival analyses, and programming in R and BUGS/JAGS/Stan. Collaboration across geographies is essential, with mentoring duties and business development ...

built that other people went on to use Broad training in empirical method, potentially from a field outside machine learning – experimental design, Bayesian inference, model selection, significance testing, uncertainty quantification Experience with automated grading and model-based judging, and a rigorous account of its failure modes and ...

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 ...