1 to 25 of 59 Permanent 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 ❯

MMM. In-depth understanding of statistical modelling and ML techniques. Experience with regression models in MMM context. Solid experience with Probabilistic Programming and Bayesian Methods. Proficiency in mining large, complex datasets using SQL and Spark. Strong knowledge of statistical techniques and mathematical foundations. Working knowledge of Pymc More ❯

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

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

ML techniques Experience with Regression based models applied to the context of MMM modelling Solid experience with Probabilistic Programming and Bayesian Methods Be an expert in mining large & very complex data sets using SQL and Spark Have in depth understanding of statistical modelling techniques and their More ❯

ML techniques Experience with Regression based models applied to the context of MMM modelling Solid experience with Probabilistic Programming and Bayesian Methods Be an expert in mining large & very complex data sets using SQL and Spark Have in depth understanding of statistical modelling techniques and their 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 ❯

marketing, and business knowledge. Collaborate with subject matter experts and stakeholders to clarify business questions and enhance feature selection. Apply probability, frequentist vs Bayesian statistics, and statistical concepts like regression, ANOVA, AB testing. Select appropriate measurement techniques/designs to answer business questions and explain trade-offs. 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 ❯

Points For: Experience working with large datasets or cloud platforms (e.g. GCP/Big Query). Exposure to advanced analytics approaches such as Bayesian or non-regression models. Familiarity with marketing measurement tools or platforms (e.g. Robyn, Meridian). Data viz skills in Power BI, Tableau, or More ❯

or consultancy environments. Bonus Points For: Familiarity with cloud platforms like GCP/BigQuery or handling large datasets. Exposure to Bayesian methods or advanced non-linear modelling approaches. Experience with open-source or proprietary MMM tools (e.g. Robyn, Meridian ). Strong data visualisation skills (Power BI 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 ❯

taking ownership of delivery Strong communication and problem-solving skills Desirable: Experience in demand forecasting or operations research Familiarity with Bayesian methods, Monte Carlo simulations, or reinforcement learning Exposure to high-scale SaaS or B2C products Why Apply? Build forecasting systems powering global commercial strategies Collaborate 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 ❯

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 ❯

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 ❯

field of machine learning. You will be apart of a highly unique research group across Natural Language Processing, Large Learning Models, deep learning, Bayesian & Signal Optimization with the exciting transition to the world of financial predication through the prism of machine learning. The most exceptional team members 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 ❯

subtract mean and divide by standard deviation) Be familiar with all regression based options within Rova. For an MMM this includes GLS, CLS, Bayesian MMM and Hierarchical Bayesian. Create response curves and optimization spreadsheet or alternatively use available tools for budget allocation. This requires knowledge of internal 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 ❯