5 of 5 Remote Probabilistic Modelling Jobs in the UK

studies, data analysis, and the development of innovative tools and services. We are looking for a full-time Consultant with technical expertise in mathematical modelling and automation applied to energy systems, particularly the GB energy system. This role is suited to an experienced modeller with a focus on technical … delivery and problem solving. As an Energy Systems Modelling Consultant, you will play a pivotal role in the delivery and future development of our consultancy services. Duties and responsibilities will include: Specifying and running energy systems simulation models, considering topics like flexibility, asset condition, forecasting, resilience, system adequacy, etc. … Research and development of modelling and simulation methodologies. Analysis and reporting of modelling results. Lead technical tasks and support/mentor more junior members of the team as required. Contribute to client meetings and internal coordination, as required, to support successful project delivery. Support the generation of cutting More ❯

studies, data analysis, and the development of innovative tools and services. We are looking for a full-time Consultant with technical expertise in mathematical modelling and automation applied to energy systems, particularly the GB energy system. This role is suited to an experienced modeller with a focus on technical … delivery and problem solving. As an Energy Systems Modelling Consultant, you will play a pivotal role in the delivery and future development of our consultancy services. Duties and responsibilities will include: Specifying and running energy systems simulation models, considering topics like flexibility, asset condition, forecasting, resilience, system adequacy, etc. … Research and development of modelling and simulation methodologies. Analysis and reporting of modelling results. Lead technical tasks and support/mentor more junior members of the team as required. Contribute to client meetings and internal coordination, as required, to support successful project delivery. Support the generation of cutting More ❯

end. Independent research and innovation in new content and technological domains. Taking a leading role in projects such as recommendation systems, churn and uplift modelling, real-time predictions, handling live streaming data, users clustering and personalization, product A/B continuous optimization, and many others. Who we are looking …/Engineering or a related field with a focus on applied statistics, AI, machine learning, or related fields with experience working with predictive and probabilistic models, clustering algorithms, classification models and time series techniques in a production environment. Proficiency with Python and all related Data Science libraries (numpy, pandas More ❯

of these countries without the need for work sponsorship. Responsibilities: Utilize, develop, and enhance simulation tooling and infrastructure to enable faster-than-real-time modelling of 1,000+ autonomous agents for various use cases such as fleet optimization, logistics, or robotics. Develop, deploy, and maintain machine learning models, with … using Docker and Kubernetes. Hands-on experience with 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 More ❯

redefine primary care while helping people live happier, healthier, and longer. Job Summary: We're seeking a Bayesian Data Scientist with deep expertise in probabilistic modeling and a strong grasp of modern AI advancements, including foundation models , generative AI , and variational inference . This role is perfect for someone … Remote/Hybrid/USA-SF, USA-remote, UK-London, UK-remote Responsibilities: Translate predictive modeling problems and business constraints into robust Bayesian or probabilistic AI solutions. Design and implement reusable libraries of predictive features and 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, and business teams to build end-to-end modeling solutions. Conduct deep-dive statistical and More ❯