26 to 31 of 31 Bayesian Methods Jobs in England

quality, customer effort, process adherence, consistency, fairness, durability of resolution and cost effectiveness. Identify the root causes of issues by combining machine learning, statistical methods and domain expertise from colleagues to understand what genuinely drives customer outcomes. Identify and test solutions Turn analytical insight into concrete proposals to improve … Python skills, with experience working with large, complex and imperfect datasets. Strong grounding in statistical analysis (e.g., classical ANOVA, non-parametric uncertainty quantification, Bayesian estimation) and causal inference, with experience designing both controlled experiments and observational studies. Experience applying machine learning, statistical modelling, NLP and LLM-based ...

endemic diseases and antimicrobial resistance.The research associate will be responsible for developing, implementing and applying artificial intelligence, machine learning, deep learning and data-mining methods to address complex research questions. They will lead the analysis of large-scale, heterogeneous datasets, including sequencing, sensor, biological and medical data, and ensure … robust, reproducible computational workflows.The postholder will be responsible for developing and applying AI methods across the following areas, demonstrated through scientific publications or other academic/industrial achievements:Generative AI (text and numerical data; excluding image, audio, video generation)Agentic AI, orchestration, and adaptive systems (continuous feedback, dynamic reasoning ...

Platform organisation and builds the evidence that helps teams make confident decisions about the data underpinning our embodied AI systems. We develop statistically robust methods, metrics and tools to determine when data-quality, annotation and evaluation signals can be trusted—and when they cannot. ð§ Your day-to-dayDefine … measurable, statistically rigorous concepts of data quality, including coverage, label quality, uncertainty, provenance and model performance.Apply statistical-inference methods to multi-rater annotation, label ambiguity, dataset coverage and black-box model evaluation.Partner with annotation, autonomy and evaluation teams to translate practical quality questions into defensible metrics.Build automated reports that ...

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 ...

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 ...