5 of 5 Probabilistic Modelling Jobs in London

with engineers and researchers to develop AI that operates reliably in complex, changing environments. The Role You’ll be responsible for designing and implementing probabilistic and machine learning models that support navigation, planning and adaptive control. A key part of the position will involve integrating these models into real … involved not just in development, but also in shaping system architecture and contributing to longer-term technical direction. Key Responsibilities Develop probabilistic and machine learning models for decision-making and control Build and refine navigation and planning systems Integrate AI algorithms into real-time robotic platforms Optimise models ...

statements and solution architectures Design, develop, and optimise advanced machine learning models including: Supervised and unsupervised learning Ensemble methods Deep learning architecture Optimisation and probabilistic models Evaluate and select appropriate algorithms based on data characteristics, performance trade-offs, scalability, and interpretability requirements Apply knowledge of deep learning architectures such … feature engineering strategies and model performance enhancement Collaborate with engineering teams to transition models into scalable production systems Mentor data scientists and uphold modelling standards, documentation, and reproducibility best practices Contribute to reusable ML frameworks, accelerators, and innovation initiatives Required Experience & Qualifications 15+ years of total professional experience , including ...

statements and solution architectures Design, develop, and optimise advanced machine learning models including: Supervised and unsupervised learning Ensemble methods Deep learning architecture Optimisation and probabilistic models Evaluate and select appropriate algorithms based on data characteristics, performance trade-offs, scalability, and interpretability requirements Apply knowledge of deep learning architectures such … feature engineering strategies and model performance enhancement Collaborate with engineering teams to transition models into scalable production systems Mentor data scientists and uphold modelling standards, documentation, and reproducibility best practices Contribute to reusable ML frameworks, accelerators, and innovation initiatives Required Experience & Qualifications 15+ years of total professional experience , including ...

complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. Working with large, structured … other data scientists, engineers and stakeholders to deliver production-ready solutions. Your work will focus on delivering high-value outcomes, including: Advanced statistical and probabilistic modelling. Machine learning and deep learning model development. Building scalable, maintainable analytical pipelines. Delivering insight and models that perform reliably in complex operational environments. ...

platform for drug and vaccine demand). This is a hands-on role for someone who is deeply comfortable working with data science models, probabilistic forecasting, and AI systems. You will own major product areas within Nexa, partner closely with engineering and modelling teams, and ensure we translate … activities for the Nexa platform. Key Responsibilities: Technical Product Ownership – Nexa: Own and execute the roadmap for core Nexa components, translating complex forecasting and modelling logic into high-quality, user-centric product features in close partnership with engineering and data science teams. Forecasting & Simulation Workflows: Enhance scenario-building, explainability ...