5 of 5 Permanent Time Series Forecasting Jobs in the Thames Valley

Science vision and roadmap , aligned with business priorities. Provide technical oversight for AI initiatives across domains: Generative AI & LLMs (fine-tuning, RAG pipelines, multi-agent systems). Predictive Analytics & Time-Series Modeling . Computer Vision & Multimodal AI . Reinforcement Learning & Optimization . Knowledge Engineering & Semantic Search . Edge AI & Real-Time AI Deployments . Act as the … experience in AI/ML, including experience in a technical leadership or team lead role . Strong knowledge (architectural & practical) of: LLMs, RAG, and AI Agents . Predictive analytics & time-series forecasting . Computer vision, multimodal learning, and geospatial AI . Reinforcement learning and optimization techniques . MLOps practices & data pipelines . Ability to review code, design More ❯

Conduct data exploration, analysis, and preprocessing for large structured/unstructured datasets. Collaborate with cross-functional teams to integrate models into business systems. Apply predictive analytics, statistical modelling, and time series forecasting to drive decision-making. Maintain clear documentation for all AI/ML pipelines and workflows . Key Skills: Solid hands-on experience in AI/ More ❯

Conduct data exploration, analysis, and preprocessing for large structured/unstructured datasets. Collaborate with cross-functional teams to integrate models into business systems. Apply predictive analytics, statistical modelling, and time series forecasting to drive decision-making. Maintain clear documentation for all AI/ML pipelines and workflows . Key Skills: Solid hands-on experience in AI/ More ❯

ML with tangeable environmental impact. As a Machine Learning Engineer, you will: Build and deploy ML models that drive decision-making and automation in complex physical systems Develop advanced forecasting and modelling approaches for challenging datasets Productionise research-grade ML using modern MLOps tooling Influence architecture and best practices across a growing technical team Given the number of candidates … PyTorch - production experience with Docker/AWS Proven track record of taking models from concept to production with measurable impact - ROI/Gains/Drops/Reducations Experience with time-series forecasting/analysis Experience with forecasting and control/optimisation techniques Experience of MLOps is highly advantageous but not an absolute pre-requisite for the More ❯

foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and More ❯