13 of 13 Probabilistic Modelling Jobs in the UK

consulting approach. Responsibilities Design, develop, and implement advanced machine learning models and AI capabilities Build and maintain knowledge graphs and causal inference systems Create probabilistic models to address complex business problems Scale AI solutions from proof-of-concept to MVP and full production Collaborate with backend engineers on data … technical specifications Required Skills & Experience Great experience combining data science with software engineering Strong expertise in machine learning, with focus on causal ML and probabilistic modelling Experience developing and implementing knowledge graphs Proficiency in scaling AI solutions from concept to production Working knowledge of backend systems, data pipelines ...

online signals, can be integrated into unified representations that support robust reasoning, including the construction and utilisation of knowledge graphs for entity linking, relationship modelling, and semantic integration. Equally important is modelling uncertainty: decision-makers often work with incomplete, noisy or fast-changing data. The project will examine … multiple AI agents can collaborate to reflect real-world investment workflows, coordinating tasks such as screening, due-diligence analysis, risk assessment and scenario modelling, with knowledge graphs potentially serving as a shared structured memory and coordination layer across agents. The design will emphasise human-AI collaboration, ensuring users retain ...

education. Technical Expertise: Postgraduate qualification in Computer Science, AI, Data Science, or related fields. Strong knowledge of AI, machine learning, deep learning, and probabilistic modeling. Proficient in Python, PySpark, data modeling, and microservices. Experience in MLOps, AI lifecycle management, and LLM orchestration on cloud platforms (AWS, GCP, Azure). ...

education. Technical Expertise: Postgraduate qualification in Computer Science, AI, Data Science, or related fields. Strong knowledge of AI, machine learning, deep learning, and probabilistic modeling. Proficient in Python, PySpark, data modeling, and microservices. Experience in MLOps, AI lifecycle management, and LLM orchestration on cloud platforms (AWS, GCP, Azure). ...

education. Technical Expertise: Postgraduate qualification in Computer Science, AI, Data Science, or related fields. Strong knowledge of AI, machine learning, deep learning, and probabilistic modeling. Proficient in Python, PySpark, data modeling, and microservices. Experience in MLOps, AI lifecycle management, and LLM orchestration on cloud platforms (AWS, GCP, Azure). ...

education. Technical Expertise: Postgraduate qualification in Computer Science, AI, Data Science, or related fields. Strong knowledge of AI, machine learning, deep learning, and probabilistic modeling. Proficient in Python, PySpark, data modeling, and microservices. Experience in MLOps, AI lifecycle management, and LLM orchestration on cloud platforms (AWS, GCP, Azure). ...

education. Technical Expertise: Postgraduate qualification in Computer Science, AI, Data Science, or related fields. Strong knowledge of AI, machine learning, deep learning, and probabilistic modeling. Proficient in Python, PySpark, data modeling, and microservices. Experience in MLOps, AI lifecycle management, and LLM orchestration on cloud platforms (AWS, GCP, Azure). ...

identify, diagnose, and predict faults in wind turbines Using a combination of signal processing, ML, and reliability-focused approaches on operational data Developing probabilistic models to assess component health and predict remaining useful life Turning complex outputs into clear, usable insights for engineering and operational teams Working closely with ...

financial technology firm in London is seeking a Head of Data Science & AI to lead the data science function. The role involves developing probabilistic models for lending decisions, embedding AI across the business, and collaborating with engineering and product teams. Candidates should have a strong background in statistics, experience ...

design and implement the 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 … 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 model training. Implement algorithms ...

design and implement the 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 … 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 model training Implement algorithms ...

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. ...

rapid prototyping and testing Strong in debugging, profiling, and optimizing code Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning Familiarity with path planning algorithms like A*, RRT, or optimization-based methods Master’s degree in Computer Science, Robotics, or a related field … dynamic changes in the environment Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigation Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty Master’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus ...