14 of 14 Bayesian Methods Jobs in England

other digital businesses.Experience with Snowflake, Power BI, Tableau or similar analytics tools.Exposure to attribution modelling, marketing mix modelling (MMM), Bayesian methods, or advanced experimentation frameworks.Work ShiftHybrid: Western Union values in-person collaboration, problem solving, and ideation whenever possible. We believe this fosters common ways of working ...

exposure to tools such as Meridian, Robyn, or PyMC Proficiency in Python and experience working with cloud platforms such as GCP Understanding of Bayesian statistics and marketing attribution concepts Ability to communicate technical findings clearly to non-technical audiences Interest in applying AI tools to enhance data ...

required to obtain UK Security Clearance. Desirable Experience Experience with any of the following would be beneficial: Statistical modelling, Bayesian methods, uncertainty estimation, or probabilistic techniques. Synthetic data generation, multi-modal AI, or action recognition. Machine learning development tools, experiment tracking, dataset management, or CI/ ...

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 ...

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 ...

command of spatial transcriptomics platforms and single-cell multi-omics analysis, with fluency in applying established analytical frameworks and the capability to develop novel methods where existing approaches are insufficient. Ideally, also with experience of integration of genomic insights with germline genetic evidence to derive causal mechanistic insight. Deep … expertise across the full spectrum of modern ML for biology: graph neural networks, Bayesian causal inference, topological data analysis, deep generative models (VAEs, diffusion models, GANs), and reinforcement learning, applied to biological discovery problems. Proven ability to design and deliver agentic AI systems integrating large language model ...

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 ...

statistics, mathematics, computer science, or equivalent experience with experience in researchProven experience applying machine learning techniques to solve business problemsProven experience in translating technical methods to non-technical stakeholdersStrong 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 visionAbility to write production code and object-oriented programmingWHO ...

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 ...

harness massive compute power and to use state-of-the-art ML techniques – published in recent conferences or developed entirely in-house – as textbook methods won’t beat the competition.ML is integral to develop successful investment management strategies; it is one of the core drivers of our overall performance … learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inferenceExcellent reasoning skills and mathematical ability are crucial: off-the-shelf methods don’t always work on our data so you will need to understand how to develop your own modelsStrong programming skills and experience working ...