23 of 23 Bayesian Methods Jobs

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 ...

build datasets suited for modelling and in-depth analysis. Design and execute measurement frameworks— including A/B testing, causal impact analysis, and multivariate methods— selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models (e.g., regression, clustering … analytics, or a related domain. Familiarity with big data querying tools such as Presto, Hive, BigQuery, or Hadoop. Exposure to Bayesian methods, causal inference, or multi‐armed bandit approaches. Experience collaborating with Machine Learning or Data Science teams to validate and scale models for business impact. ...

technical and non-technical stakeholders, translate complex model outputs into trading insights and strategic recommendations. Stay current with developments, and state-of-the-art methods in ML/optimisation relevant to energy trading. Your Profile MSc or PhD in Data Science, Statistics, Mathematics, Physics, Computer Science, Operations Research … Python (pandas, NumPy, scikit-learn, LightGBM/XGBoost, or similar); SQL and cloud-based data platforms. Experience with reinforcement learning, Bayesian methods, or time-series deep learning (LSTMs, Transformers) in a trading context. Strong experience with optimisation techniques (LP/MILP, stochastic optimisation) applied to asset ...

technical and non-technical stakeholders, translate complex model outputs into trading insights and strategic recommendations. Stay current with developments, and state-of-the-art methods in ML/optimisation relevant to energy trading. Your Profile MSc or PhD in Data Science, Statistics, Mathematics, Physics, Computer Science, Operations Research … Python (pandas, NumPy, scikit-learn, LightGBM/XGBoost, or similar); SQL and cloud-based data platforms. Experience with reinforcement learning, Bayesian methods, or time-series deep learning (LSTMs, Transformers) in a trading context. Strong experience with optimisation techniques (LP/MILP, stochastic optimisation) applied to asset ...

technical and non-technical stakeholders, translate complex model outputs into trading insights and strategic recommendations. Stay current with developments, and state-of-the-art methods in ML/optimisation relevant to energy trading. Your Profile MSc or PhD in Data Science, Statistics, Mathematics, Physics, Computer Science, Operations Research … Python (pandas, NumPy, scikit-learn, LightGBM/XGBoost, or similar); SQL and cloud-based data platforms. Experience with reinforcement learning, Bayesian methods, or time-series deep learning (LSTMs, Transformers) in a trading context. Strong experience with optimisation techniques (LP/MILP, stochastic optimisation) applied to asset ...

technical and non-technical stakeholders, translate complex model outputs into trading insights and strategic recommendations. Stay current with developments, and state-of-the-art methods in ML/optimisation relevant to energy trading. Your Profile MSc or PhD in Data Science, Statistics, Mathematics, Physics, Computer Science, Operations Research … Python (pandas, NumPy, scikit-learn, LightGBM/XGBoost, or similar); SQL and cloud-based data platforms. Experience with reinforcement learning, Bayesian methods, or time-series deep learning (LSTMs, Transformers) in a trading context. Strong experience with optimisation techniques (LP/MILP, stochastic optimisation) applied to asset ...

technical and non-technical stakeholders, translate complex model outputs into trading insights and strategic recommendations. Stay current with developments, and state-of-the-art methods in ML/optimisation relevant to energy trading. Your Profile MSc or PhD in Data Science, Statistics, Mathematics, Physics, Computer Science, Operations Research … Python (pandas, NumPy, scikit-learn, LightGBM/XGBoost, or similar); SQL and cloud-based data platforms. Experience with reinforcement learning, Bayesian methods, or time-series deep learning (LSTMs, Transformers) in a trading context. Strong experience with optimisation techniques (LP/MILP, stochastic optimisation) applied to asset ...

detection", etc Analyse data to help in better decision making Supporting initiatives for data integrity and normalization Data mining using state‐of‐the‐art methods Doing ad‐hoc analysis and presenting results in a clear manner Managing and designing the reporting environment, including data sources, security, and metadata Qualifications … Machine learning development projects Job Skills & Responsibilities: Experience in machine learning Exposure to machine learning models and corresponding statistics like K‐means, Bayesian, Clustering Strong technical skills with Python along with NumPy, Pandas, Scikit‐Learn Machine learning experience -> predictive and prescriptive modelling Data wrangling and data cleansing ...

natural-world systems: messy, noisy, sparse, nonlinear, and only partially observed. Nice to Have Experience with mechanistic models, hybrid ML, Bayesian methods, causal inference, dynamical systems, or uncertainty quantification. Experience designing benchmarks in novel or poorly defined problem spaces. Experience building models that move from research ...

data stack—from processing raw sequencing (omics) to interpreting the physics and geometry of macromolecular structures. Closed‐loop Discovery: Experience in Active Learning, Bayesian Optimization, or Optimal Experimental Design. Systems Engineering: Experience training and deploying large‐scale models or managing complex multi‐agent orchestrations. Causal Inference: Experience ...

formulate ambiguous engineering or scientific problems into well-defined ML problems with clear objectives and evaluation criteria. Curiositydriven approach to learning new technologies and methods, with emphasis on applying machine learning to realworld scientific and engineering challenges. Ability to work across a diverse range of data types. Hands … engineering applications. Exposure to edge deployment: model optimization containerized deployment to industrial hardware. Experience with design of experiments (DOE), uncertainty quantification, or Bayesian optimization. Familiarity with version control, experiment tracking, and reproducible research practicesWorking Environment In-Person, Office Environment, R&D Engineering LabOur Perks and Benefits: Robust ...

engineers • Some front-end/product sense (you care about shipping usable tools, not just notebooks) • Experience with causal inference, Bayesian methods, or mechanistic simulation ...

engineers • Some front-end/product sense (you care about shipping usable tools, not just notebooks) • Experience with causal inference, Bayesian methods, or mechanistic simulation ...

seeking a skilled Machine Learning Scientist for its London Research Centre. The role centers on advancing AI technologies, particularly in reinforcement learning and Bayesian optimisation. Successful candidates will have a PhD in Computer Science and a strong publication record in top-tier ML venues. This opportunity involves ...

edge algorithms that combine scientific and applied innovation. Candidates should have a strong academic background in Computer Science, expertise in reinforcement learning or Bayesian optimisation, and proficiency in Python. This is an exciting opportunity to contribute to high-impact AI projects within a dynamic multinational team. #J ...

Experience we're interested in: Conformal prediction, conformal inference, uncertainty quantification and statistical learning theory Probabilistic modelling, online learning, or Bayesian methods Ideal experience: Foundation models, generative AI, or multi-agent systems PyTorch, JAX, and large-scale ML systems ...

Experience we're interested in: Conformal prediction, conformal inference, uncertainty quantification and statistical learning theory Probabilistic modelling, online learning, or Bayesian methods Ideal experience: Foundation models, generative AI, or multi-agent systems PyTorch, JAX, and large-scale ML systems ...

unclear. You should apply if... You have deep expertise across a range of ML techniques (e.g. Transformer‐based NLP, Deep Learning, Tree‐based methods, Bayesian modelling) and the judgment to select solutions that balance theoretical soundness against engineering practicality. You have a proven track record ...

shelf AI. This organisation has built its reputation on proprietary Bayesian tools and deep scientific capability, using advanced sampling methods and modern AI technologies to tackle problems that standard approaches cant. If you enjoy difficult technical challenges, rigorous thinking and working at the intersection of research … Bayesian data science tools, while using modern LLM and GPT-based tools to enhance and accelerate your workflow Explore new models, methods and technologies, applying them where they add genuine value Contribute to the development of the companys core scientific and technical capabilities Collaborate with clients ...

shelf AI. This organisation has built its reputation on proprietary Bayesian tools and deep scientific capability, using advanced sampling methods and modern AI technologies to tackle problems that standard approaches can’t. If you enjoy difficult technical challenges, rigorous thinking and working at the intersection … Bayesian data science tools, while using modern LLM and GPT-based tools to enhance and accelerate your workflow Explore new models, methods and technologies, applying them where they add genuine value Contribute to the development of the company’s core scientific and technical capabilities Collaborate with ...

Build production-grade Python packages. Follow and build project scaffolds (PowerShell), follow coding standards, and reproducible workflows. Transform analyses into standardized currently best-known methods (cBKM) Process data and automate data flows; manage and optimize data structure & data bases for big data sets. Interact with product and service teams … Bachelor or Master Degree: Statistics/Computer Science/Data Science//Industrial Engineering Expert knowledge of Python, statistical modelling (frequentist and Bayesian) and data visualization Intermediate knowledge of PowerShell, R and SQL AI expert knowledge Project management Comfortable with non-recurrent, high-complexity engineering analyses ...

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 … 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 ...

recognition, including Huawei’s Gold Medals and Best Technology Breakthroughs. This role focuses on advancing the state-of-the-art in reinforcement learning, Bayesian optimisation, AI agents, large language models (LLMs), and/or vision-language models (VLMs). You will work at the intersection of fundamental … eagerness to translate cutting-edge ideas into working prototypes and real-world applications. Key Responsibilities Conduct original research in reinforcement learning or Bayesian optimisation for LLMs, leading to publications in top conferences and journals (e.g., NeurIPS, ICLR, ICML). Design and implement new algorithms and models that ...

recognition, including Huawei’s Gold Medals and Best Technology Breakthroughs. This role focuses on advancing the state‐of‐the‐art in reinforcement learning, Bayesian optimisation, AI agents, large language models (LLMs), and/or vision‐language models (VLMs). You will work at the intersection of fundamental … tier ML/AI venues: ICML, ICLR, JMLR, NeuRIPS and the like. Deep expertise in at least two of the following: Reinforcement Learning, Bayesian Optimisation, AI agents, LLMs, VLMs. Proficiency in Python and experience with at least one major ML framework (PyTorch, TensorFlow, or JAX). Ability ...

bring to the table Ability to scope and effectively deliver projects. Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering. Strong problem‐solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. Excellent collaboration and communication skills … 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 ...