1 to 25 of 37 Bayesian Methods Jobs in the UK

Job Description Summary In this role, you will understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs in neuroscience, discover actionable insights and automate process for reducing effort and time for repeated use. Moreover, you will manage the implementation and adherence … Good understanding of clinical study design principles and basic familiarity working with clinical data in a clinical trial (GxP) setting. Strong knowledge and understanding of (multivariate implementations of) statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modelling, longitudinal modelling, Bayesian methods, variable selection methods (e.g., lasso, elastic net … random forest), design of clinical trials. Familiarity with statistical and analytical methods for high dimensional data (e.g. imaging, digital, genetics or -omics data). Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. Excellent interpersonal and communication skills (verbal and writing) Ability to develop and deliver clear and concise presentations for More ❯

Data Scientist - Bayesian, Python, Pymc Leading pharmaceutical client now requires a Senior Data Scientist to drive marketing effectiveness via marketing mix modelling and other models. This role will oversee data collection, extraction, manipulation, analysis and validation ensuring data is ready for modelling. You will work closely with the Data Science team to build base models according to … is essential. Experience with Regression based models in an MMM context. Strong understanding of statistical modelling/Machine Learning techniques. Experience with probabilistic programming and Bayesian methods Good working knowledge of cloud-based data science frameworks. Rate: £688 per day Inside IR35 Duration: 6 months Location: Hybrid - 1 day per week in office near London 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/… disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, metrics, and benchmarks, 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, PyTorch Lightning, or similar frameworks Strong More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and More ❯

solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and More ❯

solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and More ❯

solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and More ❯

tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯

tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯

tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯

tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯

tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯

and data teams to ensure scalable solutions Requirements Extensive experience in data science, including applied statistics and machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP More ❯

libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modelling techniques relevant to football (player valuation, tactical analysis). Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC). Stakeholder Management: Proven success working directly with business stakeholders to define and deliver impactful solutions. What They Offer Work that More ❯

junior team members, leading research projects, and guiding collaborative efforts is a plus. Knowledge of the following machine learning domains is a plus. Generative models leveraging diffusion or Bayesian Flow Networks. Large-scale distributed machine learning training. Knowledge, experience or interest in the following biological domains is a plus. Drug discovery and protein engineering. Understanding of protein More ❯

skills Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background We are a well treated bunch, with awesome benefits! If there's something important to you that's not on this More ❯

experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus More ❯

experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus More ❯

simulation. Strong mathematical skills, including linear algebra, probability theory, and statistics. Proficiency in version control systems, particularly Git. Ability to write modular, readable, and maintainable code. Experience with Bayesian inference, object tracking, target tracking, or SLAM (Simultaneous Localization and Mapping) is desirable Excellent research literacy, with the ability to comprehend and apply the latest research papers. Experience More ❯

deals. Strong hands-on skills in Excel and PowerPoint, including financial modeling and executive presentations. Solid understanding of statistical modeling techniques such as Linear Regression, Logistic Regression, and Bayesian methods. Excellent communication skills-both written and verbal-with the ability to clearly present complex concepts to non-technical stakeholders. Leadership presence with the ability to inspire teams More ❯