21 of 21 Bayesian Methods Jobs in England

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 ...

React; Javascript/Typescript. Experience with UI/UX design principles. Experience with PyTorch or other deep‐learning libraries. An understanding of Bayesian statistics. Location On site. As an ambitious, rapidly‐growing start‐up, we’re looking for proactive, adaptable people who thrive in a fast‐paced ...

through to insight Analyse marketing, customer, and campaign data to drive performance improvements Build and apply statistical models (regression, econometrics, Bayesian methods) Support development of dashboards and visualisations Translate analytical outputs into clear business recommendations Collaborate with senior consultants and contribute to client delivery What they ...

findings Basic Qualifications PhD in business economics, engineering, analytics, mathematics, statistics, information technology or equivalent Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows Experience distilling informal customer requirements into problem definitions, dealing ...

through to multinationals, helping them secure highly sought after skill sets. Key words: Data Scientist, Algorithm Developer, Equity Research, Investments, Quantitative Research, Bayesian Statistics, Mathematics, Computer Science, Analytical Algorithms, Python. C++, Monte Carlo. ...

Proven ability to conceptualize business problems and solve them through data science solutions. Proven knowledge of AI techniques such as Bayesian methods, Clustering, Ensemble tree models, NLP, etc., with an excellent grasp of statistical concepts and methods. Strong passion for solving problems and finding patterns and ...

with time‐series modelling and industrial or IoT data. You have experience in any of: dynamical systems, reinforcement learning, system identification, optimisation or Bayesian statistics. You are used to working in a fast‐paced startup environment with an agile process. You have a degree in machine learning ...

diverse range of sources, ensuring quality and accuracy prior to use in model creation. Apply statistical and machine learning techniques such as regression, Bayesian modelling, or time-series analysis to improve our UK marketing effectiveness model. Apply learnings from the UK to developing a new model ...

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

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 Benefits Competitive salary and equity in a fast‐growing start‐up We serve lunch every weekday ...

Rust, Python and others). Confident operating at senior leadership level and influencing across functions. Desirable: Google Cloud Platform including BigQuery & AI Platform. Bayesian statistics. Agent based simulation and reinforcement learning The interview journey: 1st stage interview with two engineers from the team. Tech challenge ...

coding (Python, SQL). Deep expertise in LTV modelling and econometrics/marketing mix modelling, complemented by a strong understanding of statistics, particularly Bayesian reasoning, enabling accurate estimation and actionable insights. Technical toolkit includes experience with Bayesian approaches to machine learning, neural networks (ideally ...

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 ...

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 ...

Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian inference, APIs, SQL) Experience leading data science teams and managing project timelines Excellent communication and stakeholder engagement ...

they do with their clients Helping shape new projects based on client needs Contributing to the wider team Improving how they do MMM—tools, methods, automation Sharing knowledge and contributing to internal initiatives Living our values: Curiosity, Creativity, Excellence, Transmission, and Pleasure What our client is looking for: Your … tools like Python, R, SQL, Excel, and data visualisation platforms Experience working with large datasets and building robust models Good understanding of regression, Bayesian approaches, and advanced analytics Able to explain complex results in a simple, business-friendly way How you work Excellent communication, storytelling and presentation ...

algorithms that power Biostream’s physiological monitoring and alert systems. You will work closely with the biostatistics team to translate probabilistic and Bayesian models into deployable algorithms that operate on real‐world sensor data. The role focuses on building robust machine learning systems capable of detecting physiological … constrained connectivity. Responsibilities Design and develop machine learning algorithms for physiological signal analysis and risk detection. Work closely with the biostatistician to implement Bayesian models and probabilistic frameworks. Develop models combining vital signs, motion data, and contextual signals. Build pipelines for sensor data processing, feature extraction, and ...

algorithms that power Biostream’s physiological monitoring and alert systems. You will work closely with the biostatistics team to translate probabilistic and Bayesian models into deployable algorithms that operate on real-world sensor data. The role focuses on building robust machine learning systems capable of detecting physiological … constrained connectivity. Responsibilities Design and develop machine learning algorithms for physiological signal analysis and risk detection Work closely with the biostatistician to implement Bayesian models and probabilistic frameworks Develop models combining vital signs, motion data, and contextual signals Build pipelines for sensor data processing, feature extraction, and ...

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 ...

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 ...

tools and datasets to characterise small-molecule interactions with intrinsically disordered proteins. Based just a short walk from Kings Cross station, Bind leverages interdisciplinary methods that span experimental biophysics – with a strong focus on nuclear magnetic resonance (NMR) spectroscopy – as well as computational approaches and cellular studies. You will … built models by implementing automated, streamlined, and efficient software solutions in line with best practices Utilise active learning, Bayesian, and bootstrapping methods to achieve robust performance in low-data regimes, and make use of distributed training methodologies for large models Build model-deployment and job-launching ...