1 to 25 of 38 Bayesian Methods Jobs in England

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. … 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 More ❯

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 Work towards long-term research goals, while identifying intermediate milestones Build relationships and collaborate with academics and institutions Explore new … research experience, or 5 or greater years of work experience (actual job title/position will be commensurate to experience) Good background in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with Deep Learning … abilities in Python and/or C++ Preferred Qualifications: 2D & 3D Generative AI Reinforcement Learning LLMs and Natural Language Processing Computational geometry and geometric methods (e.g. shape analysis, topology, differential geometry , discrete geometry , functional mapping, geometric deep learning, graph neural networks) Multi-modal deep learning and/or information More ❯

Python skills; familiarity with R for MMM. Expertise in regression modeling, statistical and ML techniques . Experience with probabilistic programming, Bayesian methods, and MCMC. Proficient in SQL and/or Spark for large-scale data mining. Solid understanding of statistical foundations and mathematical modelling. Familiarity with More ❯

Python skills; familiarity with R for MMM. Expertise in regression modeling, statistical and ML techniques . Experience with probabilistic programming, Bayesian methods, and MCMC. Proficient in SQL and/or Spark for large-scale data mining. Solid understanding of statistical foundations and mathematical modelling. Familiarity with More ❯

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 … 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 More ❯

ll work on a broad spectrum of problems ranging from marketing measurement to algorithmic optimization. Our solutions combine advanced ML, causal inference, and Bayesian modeling to drive marketing effectiveness at scale. The Challenge: While you'll initially focus on building YouTube as Amazon's next variable marketing … audience targeting and content optimization Customer behavior modeling frameworks Why You'll Love It: Work on diverse problems spanning ML, causal inference, and Bayesian statistics Tackle challenges across multiple scientific domain and use cases Develop novel approaches for ML & science, specially within marketing Build solutions that directly … markets If you're excited about advancing the state of the art in marketing science through innovative applications of ML, causal inference, and Bayesian statistics, while working on diverse problems that directly impact millions of customers, we want to hear from you. BASIC QUALIFICATIONS PhD, or a More ❯

practical solutions for predictive analytics. Experience in solution design, architecting and outlining data analytics pipelines and flows. Advanced Mathematics skills including experience with Bayesian statistics, linear algebra and MVT calculus, advanced data modelling and algorithm design experience. Design and deployment experience using Tensor Flow, Spark ML, CNTK More ❯

reinforcement learning frameworks such as OpenAI Gym or Stable-Baselines3. Practical knowledge of optimization algorithms and probabilistic modeling techniques (e.g., Bayesian methods, Gaussian Belief Propagation). Experience integrating models into real-time decision-making systems or multi-agent RL environments (MARL). Exposure to spatiotemporal data More ❯

tools such as Google Looker and working with Google's BigQuery. Experience in design and evaluation of A/B tests. Familiarity with Bayesian statistics, especially for hypothesis testing. Experience with application of optimization theory or reinforcement learning based on automated A/B testing. Projects you More ❯

Bonus: Experience implementing solutions in a production environment (e.g., continuous integration). Experience with Python. (Note: we mostly work in Python.) Experience with Bayesian statistics. The salary We expect to pay from £70,000 - £90,000 for this role. But, we're open-minded, so definitely include More ❯

Bonus: Experience implementing solutions in a production environment (e.g., continuous integration). Experience with Python. (Note: we mostly work in Python.) Experience with Bayesian statistics. The salary We expect to pay from £70,000 - £90,000 for this role. But, we're open-minded, so definitely include More ❯

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 More ❯

flexibility to learn by iteration. Desirable Attributes Masters/PhD in STEM subject. Understanding of functional and object-oriented programming paradigms. Experience with Bayesian models, Markov chains and multivariate time-series modelling. Experience with widely used probabilistic programming and machine learning libraries such as Stan, PyMC3, Scikit More ❯

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. By joining More ❯

environment constantly subject to innovation. How will you make an impact: Estimating uncertainty and error propagation in our models; Applying Bayesian methods for the calibration of complex process-based models; Designing sampling strategies for our data collection campaigns; Evaluating the quality and quantity of our data … in one of the relevant Science fields mentioned above; A baseline understanding of greenhouse gas accounting frameworks and methodologies; Strong theoretical background in Bayesian Statistics; Knowledge or experience working with crop, pedometrics, or process-based models; Experience coding in Python; Handling unstructured/imbalanced data. What's More ❯

probabilistic representations for diverse ML tasks. Build and optimize tools for scalable probabilistic inference under memory, latency, and compute constraints. Apply and innovate on methods like Bayesian neural networks , variational autoencoders , diffusion models , and Gaussian processes for modern AI use cases. Collaborate closely with product, engineering … uncertainty quantification, and responsible AI. Requirements/Qualifications: Strong experience in Bayesian inference and probabilistic modeling : PGMs, HMMs, GPs, MCMC, variational methods, EM algorithms, etc. Proficiency in Python (must) and familiarity with PyMC, NumPyro, TensorFlow Probability , or similar probabilistic programming tools. Hands-on experience with classical … ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods . Solid understanding of feature engineering, dimensionality reduction, model construction, validation, and calibration. Experience with uncertainty quantification and performance estimation (e.g., cross-validation, bootstrapping, Bayesian credible intervals). Familiarity with database and data More ❯

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 More ❯

Python for data analysis. Statistical mindset with the ability to setup, run and analyse RCTs and split tests. Extra bonus for knowledge of Bayesian Statistics. Experience optimising user journeys and driving customer engagement. Passionate about helping small businesses thrive-belief in our mission is important! The salary More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

and Mr Green and we're looking for an experienced (London or Leeds based) Data Scientist to be responsible for developing AI/ML methods, processes and systems to extract knowledge or insights to drive the future of artificial intelligence. What you will be doing: Applying and/or … developing statistical modelling techniques (such as deep neural networks, Bayesian models, Generative AI, Forecasting), optimization methods and other ML techniques. Converting data into practical insights. Analysing and investigating data quality for identified data and communicate it to the Product Owner, Business Analyst, and other relevant stakeholders. More ❯

junior team members, leading research projects, and guiding collaborative efforts is a plus. Knowledge of Machine Learning Domains: Generative models leveraging diffusion or Bayesian Flow Networks. Modelling multimodal data. Large-scale distributed machine learning training. Knowledge, Experience, or Interest in Biological Domains: Drug discovery and protein engineering. More ❯