4 of 4 Permanent Data Science Jobs in Stockport

chain. This role is fully remote in UK, with full work authorization already in effect. No Visa sponsorship is available. Job Description In a data-driven and AI-oriented environment, you will be responsible for the design, industrialization, and optimization of inter-application data pipelines. You will … involved in the entire data chain, from data ingestion to its use by data science teams and AI systems in production within a human-sized and multidisciplinary team. This role is within Process Intelligence (PI) team that combines functions such as Process Mining, Real Time Monitoring ...

front end of enterprise software or SaaS products that are used by large enterprises. A small highly collaborative product team consisting of designers and data scientists within a growing consultancy so the ideal candidate will take ownership of the development of the product (alongside the product lead … excellent communicator, able to contribute to the roadmap and steer technical decisions. You will be expected to: ● Develop new features working with the data science ● Develop bug fixes and security patches promptly ● Collaborate and contribute to product feature planning (from a technical perspective) ● Lead implementation of testing infrastructure ...

future proof, and expand their revenue opportunities. Their product empowers lawyers and finance teams to maximise value from engagements through: Pricing agents that create data-driven, lawyer-friendly quotes. Management tools that predict overruns and help avoid costly late bills. Enrichment engines that clean and structure messy legal datasets … join. The Role: AI/ML Engineer – Agentic Systems You will design and deliver intelligent agentic workflows, leveraging frontier LLMs. Working with their data scientists and backend engineers, you'll be responsible for making unstructured legal data usable, scalable, and impactful. This is not a prototyping role ...

robust engineering, governance, and scalability. Responsibilities Design, build, and deploy machine learning models into production within a Financial Services environment Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance … Python skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn) Experience deploying and supporting ML models in production Solid understanding of data pipelines, versioning, testing, and software engineering best practices Experience working with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk ...