51 to 75 of 137 Bayesian Methods Jobs in England

don't tick all the boxes, you'll certainly learn on the job! Essential MSc or PhD, or equivalent experience in a quantitative field Deep theoretical knowledge of statistical methods and ML algorithms and their practical applications. Strong proficiency in SQL and Python, especially with core ML libraries (e.g. scikit-learn, XGBoost, SciPy, PyTorch) Extensive hands-on experience in … version control (e.g. Git), code reviews, CI/CD pipelines, unit testing, and collaborative workflows such as Agile. Experience with optimisation techniques (e.g. gradient descent, Bayesian methods, Lagrangian methods etc) and their practical application Experience in UK General Insurance (Motor and/or Home), with a solid understanding of pricing principles and regulatory governance. Familiarity More ❯

Mix Modeling (MMM) work comprehensively. Must have led multiple projects on MMM analytics. Experience in pricing and promotion analytics is a plus. Must have experience with Databricks. Implemented Bayesian regression on Python. Exposure to libraries like numpy, pandas, sklearn, pymc3. Hands-on experience in PowerPoint/Excel is a must. Strong logical, analytical, and problem-solving skills. More ❯

managers and various business stakeholders to ensure top-quality outcomes to meet internal objectives. Investigate and adopt innovative concepts that offer tangible benefits. Employ techniques like Deep Learning, Bayesian Modelling, Large Language Models, Product embedding, Recommendation Systems, and Computer Vision. To be successful in the role, you'll need: 5+ years of hands-on data science experience. More ❯

Strong data analysis skills in Python or R Strong programming skills in Python Prior experience training and analyzing Machine Learning models, e.g. neural networks, transformer architectures, XGBoost models, Bayesian networks, etc The ability to prototype fast to test ideas quickly The ability to reason with data and share insights with relevant stakeholders in a clear way Be More ❯

business stakeholders to scope and define projects. Knowledge of version control systems, particularly Git, with experience managing codebases and collaborating in team environments. Nice to haves: experience with Bayesian modelling and probabilistic programming libraries such as PyMC; proven ability in the creation and deployment of fraud detection models; familiarity with Amazon Sagemaker and its various features used More ❯

Google Analytics, Adobe Analytics, and marketing automation platforms Experience leading a team of marketing analysts/marketing scientists Advanced analytics techniques: expertise in regression models (e.g. ridge regression, Bayesian regression), time series analysis, forecasting + end to end MMM ownership experience Strong SQL and Python Excellent leadership and project management skills, with the ability to lead cross More ❯

ML/Stats for them to 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 solutions quickly. Excellent collaboration … in computer science, machine learning, 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 spatiotemporal data (VAEs, Diffusion Models … Bayesian non-parametric, scaling to large datasets, etc.). Ideally, >2 years of experience in a data-driven role, with exposure to: building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; developing models for bespoke problem settings that involve high-dimensional data More ❯

mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an More ❯

doing causal inference/segmentation Ability to explain ideas and present results to non-technical audiences Strong stakeholder management skills Experience with marketing mix models and/or Bayesian time series would be a big plus Strong theoretical understanding and experience with key classification and regression models is a plus Please note this role is offered on More ❯

mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an More ❯

mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an More ❯

management Key Experience: Strong academic background with a minimum 2:1 Degree in Computer Science (or similar) Strong numerical background with a knowledge of key statistical principles – eg Bayesian and frequentist statistics Experience with multiple programming languages including SQL and Python Familiarity with large language models Understanding of ML algorithms This is an excellent opportunity for a More ❯

Understands complex and critical business problems from a variety of stakeholders and business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the definition, implementation and adherence to the overall … biostatistics, or other quantitative field (or equivalent). More than 6 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net More ❯

sensing, or statistical modelling 3+ years of experience in climate risk, catastrophe, or related modelling domains Bonus Experience Expertise in exposure and vulnerability within catastrophe models Background in Bayesian statistics, Extreme Value Theory, or uncertainty quantification Knowledge of machine learning techniques for climate risk Familiarity with cloud computing (AWS, GCP) ? Hybrid working (3 days/week on More ❯

sensing, or statistical modelling 3+ years of experience in climate risk, catastrophe, or related modelling domains Bonus Experience Expertise in exposure and vulnerability within catastrophe models Background in Bayesian statistics, Extreme Value Theory, or uncertainty quantification Knowledge of machine learning techniques for climate risk Familiarity with cloud computing (AWS, GCP) ? Hybrid working (3 days/week on More ❯

Research Engineer - Bayesian Optimisation (Contractor) Join to apply for the Research Engineer - Bayesian Optimisation (Contractor) role at Huawei Technologies Research & Development (UK) Ltd Research Engineer - Bayesian Optimisation (Contractor) 1 year ago Be among the first 25 applicants Join to apply for the Research Engineer - Bayesian Optimisation (Contractor) role … at Huawei Technologies Research & Development (UK) Ltd Get AI-powered advice on this job and more exclusive features. Job Description Job Title Research Engineer – Bayesian Optimization Department/Group Reinforcement Learning Team Reports To Haitham Ammar Manager Position No Location London Position Type Full time 37.5 hours per week About Huawei Research And Development UK Limited Founded … technologies. We invite you to join us on this exciting journey and drive your career forward. Job Summary Huawei is looking for a Research Engineer with experience in Bayesian optimization . We wish to recruit exceptional candidates to pursue research in various aspects of reinforcement learning and Bayesian optimization for autonomous decision-making under More ❯

United Kingdom 1 month ago London, England, United Kingdom 1 week ago London, England, United Kingdom 1 day ago London, England, United Kingdom 3 weeks ago Research Engineer - Bayesian Optimisation (Contractor) London, England, United Kingdom 1 year ago London, England, United Kingdom 1 week ago London, England, United Kingdom 1 week ago London, England, United Kingdom More ❯

Our client is revolutionising healthcare for millions of patients worldwide. They are at the forefront of wearable technology, connecting patients and physicians with continuous, data-driven dialogue. This unique position offers daily directed guidance that redefines primary care while helping More ❯

in the AI Lab. Responsibilities Develop new ML models and AI techniques Lead on research projects within a global team Review relevant AI/ML literature to identify emerging methods, technologies, and best practices Explore new data sources and discover techniques for best leveraging data Minimum Qualifications A Master's or PhD in a field related to AI/… Architecture or related disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, and deploying production-ready solutions) Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Strong More ❯

in the AI Lab. Responsibilities Develop new ML models and AI techniques Lead on research projects within a global team Review relevant AI/ML literature to identify emerging methods, technologies, and best practices Explore new data sources and discover techniques for best leveraging data Minimum Qualifications A Master's or PhD in a field related to AI/… Architecture or related disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, and deploying production-ready solutions) Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Strong More ❯

machine learning techniques, such as clustering, classification, and regression Previous experience presenting information to key stakeholders Nice to haves...... Previous experience using Generalised Linear Regression Modelling Knowledge of Bayesian Statistics and Monte Carlo Simulation Experience with Azure: Azure Databases, Azure Databricks Proficient use of VBA's Apply for this job #J-18808-Ljbffr More ❯

machine learning techniques, such as clustering, classification, and regression Previous experience presenting information to key stakeholders Nice to haves...... Previous experience using Generalised Linear Regression Modelling Knowledge of Bayesian Statistics and Monte Carlo Simulation Experience with Azure: Azure Databases, Azure Databricks Proficient use of VBA's Please note due to the large volume of applications we receive More ❯

technical audiences. A self-starter who thrives in a fast-paced R&D environment. Experience in catastrophe modelling, especially around exposure and vulnerability. Applied statistical skills such as Bayesian statistics, uncertainty quantification, or Extreme Value Theory. Knowledge of machine learning applications in climate risk. Familiarity with cloud platforms (e.g., AWS, Google Cloud). If this role looks More ❯

technical audiences. A self-starter who thrives in a fast-paced R&D environment. Experience in catastrophe modelling, especially around exposure and vulnerability. Applied statistical skills such as Bayesian statistics, uncertainty quantification, or Extreme Value Theory. Knowledge of machine learning applications in climate risk. Familiarity with cloud platforms (e.g., AWS, Google Cloud). If this role looks More ❯

libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a plus. Familiarity with statistical confidence testing. Understanding and expertise in statistical modelling techniques is a plus. Strong communication, stakeholder management, and people management skills. Ability More ❯