1 to 25 of 68 Bayesian Methods Jobs in England

biggest brands in the US. They are completely rebuilding their flagship products around Bayesian frameworks, moving away from legacy frequentist methods to process tens of millions of data points with higher accuracy and speed. They need a Senior Data Scientist to set the technical standard … Bayesian methods across a growing 25-person UK team. You will directly own core models, choose the best methods for the job, and see your work guide major commercial decisions. Drive Model Strategy: Select and build the right Bayesian, frequentist ...

Postdoc in Bayesian machine learning, AstraZeneca, Cambridge, UK Mar 29, 2018 PREDICTING DRUG TOXICITY WITH BAYESIAN MACHINE LEARNING MODELS We’re currently looking for talented scientists to join our innovative academic-style Postdoc. From our centre in Cambridge … uncertainty in the inputs and propagate this uncertainty into the predictions. In addition, you will promote the use of Bayesian methods across safety pharmacology and biology more generally. You are also expected to present your findings at key conferences and in leading publications This project ...

deployment in laboratories, hospitals, and public health organisations worldwide. Your Role: As a (Senior) Scientist, you will design, develop, and evaluate novel computational methods for translating metagenomic sequencing data into actionable results in a clinical or public health context. You will develop algorithms and AI/ML methods … Develop ML/AI techniques to address real-world problems in the pathogen genomics space, in collaboration with scientists across EIT Validate and benchmark methods using public and internal datasetsWork with bioinformaticians and software engineers to implement methods in scalable, reproducible, and modular workflows Communicate technical work clearly ...

analysis Have in depth understanding of statistical modelling/ML techniques for time series forecasting (ARIMA, ETS, Prophet, Time Series pattern detection, and ML methods) Strong experience with Causal inference, Intervention analysis, Counterfactuals Estimation, Optimization and Scenarios simulation Solid experience with Probabilistic Programming and Bayesian Methods ...

least 3 data or ML products from problem definition to production deployment and monitoring.* Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.* Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale.* Proficiency in SQL, Python, and familiarity with ...

replacement for understanding. Writes precise instructions, reviews AI-generated diffs critically, and verifiesbehaviourbefore committing. Experience with and/or knowledge of Bayesian models, state space models, filtering and smoothing, computationalstatisticsand approximate inference methods. Experience with and/or knowledge of machine and statistical learning, deep neural networks ...

Excel, and visualization tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Strong understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Skilled in handling large datasets, optimizing pipelines, and delivering high-quality outputsTrack record of translating complex model results into ...

least 3 data or ML products from problem definition to production deployment and monitoring. Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics. Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale. Proficiency in SQL, Python, and familiarity with ...

least 3 data or ML products from problem definition to production deployment and monitoring.* Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.* Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale.* Proficiency in SQL, Python, and familiarity with ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Deep understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Proven ability to handle large datasets, optimise pipelines, and deliver high-quality outputs. Track record of translating complex model ...

both technical and non-technical audiences. A proven track record of turning business problems into measurable outcomes. Nice to Have Experience with Bayesian modelling, optimisation algorithms or multi-armed bandits. Exposure to Generative AI, LLMs or agentic AI systems. MLOps experience, including CI/CD, model monitoring ...

stakeholders Hands-on experience with a range of models, such as time-series forecasting, gradient boosting, clustering, NLP and Bayesian methods Strong MLOps: orchestration, experiment tracking, hyperparameter tuning and automated retraining pipelines Object-oriented Python, Polars or PySpark, and data versioning (e.g. DVC), plus experience designing ...

avoid technical debt Deep knowledge of a handful of machine learning algorithms — not breadth for its own sake, but real understanding of a few methods and when they apply Able to systematically debug unfamiliar code, using AI tooling to accelerate rather than to guess while still understanding problem fully … tooling Familiarity with automated QA tooling and test coverage practices Any experience with marketing, ecommerce, or advertising data Exposure to Bayesian methods, marketing mix modelling, or experimental design Not required You do not need prior experience with marketing mix modelling, attribution methodology, incrementality testing, or Bayesian ...

pricing models.* Turning pricing opportunities into measurable hypotheses, experiments and production changes.* Evaluating pricing performance through backtesting, online testing and commercial metrics.* Developing Bayesian, multi-armed bandit and other optimisation approaches for dynamic pricing.* Working with commercial, finance and product teams to understand pricing performance and recommend … code, testing and code review, alongside strong SQL.* A solid grounding in machine learning techniques such as gradient boosting, GLMs, Bayesian methods and multi-armed bandits, or comparable experimentation and optimisation methods.* Experience designing, running and evaluating pricing experiments using both commercial and statistical measures. ...

attribution and customer acquisition economics. Commercially minded, with the ability to influence marketing strategy. An AI-first approach to data science. Experience with Bayesian modelling, value-based bidding or LTV modelling would be advantageous. Package: £70,000-£90,000 + bonus and benefits Location: Fully remote within ...

some ‘nice to haves’ are: Experience with UI/UX design principles. Experience with PyTorch or other deep-learning libraries. An understanding of Bayesian statistics. Location: This role is on-site at our Exeter or Bristol office. As an ambitious, rapidly-growing start-up, we’re looking ...

some ‘nice to haves’ are: Experience with UI/UX design principles. Experience with PyTorch or other deep-learning libraries. An understanding of Bayesian statistics. Location: This role is on-site at our Exeter or Bristol office. As an ambitious, rapidly-growing start-up, we’re looking ...

international clients, from data strategy and collection to modelling, insights, and activation. Apply econometrics, regression, Bayesian statistics, and machine learning methods to analyse marketing and customer data. Collaborate closely with Managers to understand the project scope, structure, analytical approaches, manage operations and ensure timely delivery. Build … similar tools. Experience with Databricks, Azure, or other cloud/data platforms is a plus. Solid understanding of econometrics, regression analysis, Bayesian statistics, or other advanced modelling techniques. Experience translating data and model outputs into actionable business recommendations. Comfortable handling large datasets, optimizing data pipelines, and delivering ...

reasoning with practical software engineering to calibrate models against measurements, test predictions on independent cases and build uncertainty analysis into the simulation workflow. Your methods and software will help engineers and investors understand what the simulator predicts and the limits of those predictions. We welcome people from AI systems … and other fields where simulation is tested against experiments. You might bring systems engineering experience and an interest in developing uncertainty methods, or experience in mathematical modelling and scientific computing that you want to apply to AI infrastructure. What you will do Develop and implement methods to calibrate ...

biggest brands in the US. They are completely rebuilding their flagship products around Bayesian frameworks, moving away from legacy frequentist methods to process tens of millions of data points with higher accuracy and speed. They need a Senior Data Scientist to set the technical standard … Bayesian methods across a growing click apply for full job details ...

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 Visualization, data skills, SQL, matplotlib, etc. Unleash Your Potential When you join Salesforce ...

world physical systems. Must-Have Requirements Strong Python experience, particularly for data pipelines. Experience with probabilistic time-series forecasting , including Bayesian methods, PyMC, Amazon DeepAR or similar. Experience working with small or scarce datasets for distribution prediction. Proven ability to build data pipelines/database architectures ...

engineers, and deploy models at scale while ensuring responsible AI governance. You will apply time series forecasting, causal inference, and Bayesian methods, build reusable assets for Forecasting and Optimization, and mentor junior data scientists. #J-18808-Ljbffr ...

with a proven record of success in online data science competitions, such as Kaggle. Experience in deep learning, reinforcement learning, non‐convex optimisation, Bayesian non‐parametrics, NLP or approximate inference. Excellent reasoning skills and mathematical ability. Strong programming skills and experience working with Python, Scikit‐Learn, SciPy ...

data pipelines using dbt, Airflow, and Snowflake. Beyond querying, you use Python for advanced automation and forecasting, and you apply statistical rigor (e.g. Bayesian statistics, causal inference) to solve complex product problems. Commercial & Risk Mindset: You possess deep commercial fluency, understanding the unit economics of a fintech ...