51 to 75 of 75 Bayesian Methods Jobs in England

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 ...

design experiments, model customer behaviour, analyse large datasets across the funnel, and collaborate with commercial, strategy and product colleagues. Experience with causal inference, Bayesian thinking, and AI-driven analytics is highly valued. #J-18808-Ljbffr ...

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 ...

unclear. You should apply if... You have deep expertise across a range of ML techniques (e.g. Transformer‐based NLP, Deep Learning, Tree‐based methods, Bayesian modelling) and the judgment to select solutions that balance theoretical soundness against engineering practicality. You have a proven track record ...

path forward is unclear.You should apply if...You have deep expertise across a range of ML techniques (e.g. Transformer-based NLP, Deep Learning, Tree-based methods, Bayesian modelling) and the judgment to select solutions that balance theoretical soundness against engineering practicality.You have a proven track record ...

production scale for soccer or sports betting Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods Minimum of 3+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports ...

grow and you to mentor. What you bring to the table Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering. Ability to scope and effectively deliver projects. Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend … applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following: operator learning (neural operators), or other probabilistic methods for PDEs; geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data; generative models for geometry and ...

and strategic level. Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling . Understanding of Bayesian approaches and modeling frameworks. Proven ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership … global scale. Responsibilities Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing analytics methods and data science. Partner with internal teams in advanced analytics work including experimentation, measurement and modeling. Identify patterns and behaviors that are effective predictors ...

helps and where it doesn’t. The requirements Essential: Statistical foundations . Strong grounding in probability and statistics, with an understanding of Bayesian reasoning and experience applying hierarchical modelling or decision-making under uncertainty. Causal inference . Experience separating signal from noise in observational and experimental data. … different audiences. Bonus: Modelling depth . Experience building or adapting statistical or ML models, with an interest in understanding what’s happening underneath. Stochastic methods . Familiarity with stochastic modelling concepts as they apply to inference, time series, or uncertainty. Funnel and marketplace experience . Experience with conversion funnel ...

Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing analytics methods and data science.Partner with internal teams in advanced analytics work including experimentation, measurement and modeling. Identify patterns and behaviors that are effective predictors of performance and critical … tactical and strategic level.Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling .Understanding of Bayesian approaches and modeling frameworks.Proven ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross ...

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 ...

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 ...

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 ...

performance, and memory utilization across heterogeneous hardware clusters using expressive hardware DSLs (e.g., TileLang, Triton). Advance the LLM orchestration loop and leverage Bayesian optimization to automate the search, generation, and continuous improvement of high-performance NPU kernels. Key Responsibilities Design and execute scaled RL finetuning workflows … focus on Machine Learning. Deep proficiency in PyTorch and experience writing custom training loops and data pipelines. Hands-on experience with RLHF/RLVF methods (e.g., PPO, GRPO) and an understanding of policy optimization dynamics. Technical familiarity with at least two of the following: DeepSpeed, FSDP, verl or trl. ...

energised by the opportunity to grow.What You’ll DoExperimentationDesign and analyse A/B tests across Viator’s marketplace, applying sound statistical methods to interpret results and support confident decision-makingChampion experimentation best practices: power calculations, guardrail metrics, and multiple testing corrections.Develop your mastery of causal inference and advanced … data science, analytics, or quantitative research role at a data-driven organization; strong product analysts who are actively upskilling in data science methods are encouraged to applyAdvanced SQL skills and hands-on experience querying and manipulating large datasetsProficiency with data visualisation tools (Tableau, Looker or equivalent) Experience with ...

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 ...

efficient data transformations using distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems.Mentor junior team members and utilise model explainability methods to drive feature performance improvements.About You5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale business problems.Deep … understanding of frequentist and Bayesian statistics, plus supervised and unsupervised modelling techniques.Proven experience modelling complex interactions (e.g., cluster or network effects).Expertise in model explainability to tune feature engineering and understand feature interactions.Ability to write high-quality, production-grade Python code and collaborate effectively with non-technical ...

data transformations using distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems. Mentor junior team members and utilise model explainability methods to drive feature performance improvements. About You 5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale … business problems. Deep understanding of frequentist and Bayesian statistics, plus supervised and unsupervised modelling techniques. Proven experience modelling complex interactions (e.g., cluster or network effects). Expertise in model explainability to tune feature engineering and understand feature interactions. Ability to write high-quality, production-grade Python code ...

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 ...

novel safety evaluations in high-impact domains such as CBRN and Cyber to quantify emerging risks.Executing original technical research in AI safety evaluation methods, taking ideas from concept to publication.Shaping the R&D agenda by identifying strategic opportunities to advance safety evaluation methodology across Faculty and the broader ecosystem.Contributing … testing, jailbreaking, indirect prompt injection, and assessing the robustness of model safeguards.Strong foundational skills in experimental design, statistical analysis, and uncertainty quantification, including Bayesian methods.Deep knowledge of language models, generative AI architectures, training methodologies, and safety mitigation techniques.Solid Python proficiency combined with the engineering discipline required ...

novel safety evaluations in high-impact domains such as CBRN and Cyber to quantify emerging risks. Executing original technical research in AI safety evaluation methods, taking ideas from concept to publication. Shaping the R&D agenda by identifying strategic opportunities to advance safety evaluation methodology across the company and … jailbreaking, indirect prompt injection, and assessing the robustness of model safeguards. Strong foundational skills in experimental design, statistical analysis, and uncertainty quantification, including Bayesian methods. Deep knowledge of language models, generative AI architectures, training methodologies, and safety mitigation techniques. Solid Python proficiency combined with the engineering discipline ...