10 of 10 Remote/Hybrid Bayesian Methods Jobs in the UK excluding London

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 ...

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 ...

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 ...

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 ...

early clinical development to regulatory approval and lifecycle work. You will provide expert statistical consultation on trial design and analysis, develop and apply advanced methods, and translate complex quantitative concepts into clear insights for cross-functional partners. You will also contribute to scientific communications and external collaboration through publications … doProvide statistical consultation on clinical trial design and analysis across multiple development stages and therapy areas.Develop and implement innovative statistical approaches, including model-based methods using frequentist and Bayesian techniques.Run or guide advanced analyses and simulations to inform design options, sample size, and power trade-offs.Communicate ...

knowledge sharing across the discipline. What we're looking forExperience as a Data Analyst (or similar role) within consumer-facing product teams Experience applying methods for statistical inference (e.g. Bayesian, Frequentist) and analysing A/B tests Experience in planning and completing analytical tasks on time ...

each stage of the consumer’s lifecycle. Experience overseeing experimentation programmes and practices that inform product or business decisions. A good understanding of methods for statistical inference (e.g. Bayesian, Frequentist) and familiarity with predictive analytics techniques is highly beneficial. Working knowledge of common analytics tools used ...