This role involves owning full-solution validation, minimizing time to production, and ensuring Day 2 stability for large-scale GPU clusters. You will work closely with customers, partners, and cross-functional teams to architect, implement, and optimize Kubernetes-based platforms and HPC systems.
This role involves owning full-solution validation, minimizing time to production, and ensuring Day 2 stability for large-scale GPU clusters. You will work closely with customers, partners, and cross-functional teams to architect and implement Kubernetes-based platforms, automate processes, and provide consultative guidance across the entire stack.
This role involves working closely with Databricks' largest and most complex customers to design and implement data solutions on the Databricks Lakehouse platform. The candidate will lead technical engagements, develop customer-specific strategies, and act as a trusted advisor during the sales and adoption process. Activities include leading proofs-of-concept, delivering technical workshops, and collaborating with cross-functional teams to drive platform adoption across diverse industries.
This role involves building and deploying predictive and statistical models, developing customer segmentation and churn models, and delivering forecasting and customer analytics solutions. You will work across the full Data Science lifecycle, from problem definition to deployment, and collaborate with analysts, engineers, and business stakeholders to present insights and recommendations.
This role involves working in a growing data and analytics team, delivering insights and analysis that support data-driven marketing and commercial decisions. You will build and apply predictive models, prepare and manipulate data, and translate findings into clear stories for various stakeholders.
This role involves developing and deploying machine learning models for financial market predictions, building AI systems to extract information from financial documents, and contributing to data infrastructure. The position requires a strong quantitative background and experience in machine learning, statistical modeling, and data engineering.
This role involves owning the full machine learning lifecycle for production systems that enhance customer experience in online grocery, including personalisation, recommendations, and search ranking. The engineer will work within a cross-functional data science team to build scalable, reusable ML components while championing data quality, MLOps best practices, and platform thinking. A strong focus is placed on system reliability, technical leadership, and collaboration across disciplines.
This role involves building and deploying machine learning models to solve business challenges in financial services, collaborating with data engineering and analytics teams to create reproducible pipelines, and translating complex data into actionable insights. The position offers the opportunity to shape the data science practice within an established company.
This role involves end-to-end ownership of existing analytics and production data science models for UK and Canadian markets, with a focus on revenue monitoring, partner performance, email campaigns, and experimentation. The Data Scientist will maintain and troubleshoot live systems rather than build new models, ensuring reliability and clear communication with cross-functional teams. The position requires strong operational discipline and technical maintenance of established pipelines and reporting.
You will lead and support the delivery of AI, GenAI, and data science projects, working closely with clients to understand their business challenges and deliver innovative solutions. Your role involves applying modern data science techniques, collaborating with multidisciplinary teams, and contributing to business growth through proposals and thought leadership.
This role involves leading the design and delivery of modern data and AI solutions within complex transformation programmes for enterprise clients. The candidate will architect end-to-end data platforms, integrate AI/ML capabilities, and ensure robust data governance across cloud and legacy systems. A key focus is bridging technical data architecture with business strategy while advising senior stakeholders.
The Finance Data Scientist will work closely with the Finance and Analytics Engineering teams to ensure accurate financial reporting, forecasting, and analysis. Key responsibilities include revenue and ARR reconciliation, pricing and packaging experiments, and translating finance questions into actionable insights.
This role involves designing, building, and enhancing a secure and scalable Databricks data platform, developing data pipelines, and contributing to platform architecture and best practices. You will work closely with Product, Analytics, and Data Science teams to deliver effective data solutions and support platform operations.
You will design, build, and optimize scalable data pipelines and platforms using modern cloud tooling. Your work will involve developing and maintaining data warehouses, ensuring data quality, and collaborating with Data Scientists, Analysts, and Product teams to deliver usable datasets.
This role involves analysing manufacturing, quality, and product performance data to uncover trends and drive improvements. The Data Scientist will develop analytical models and dashboards, apply machine learning and statistical techniques, and collaborate with engineering and digital teams to support data-driven decision-making. A key focus is translating complex data into actionable insights for both technical and non-technical stakeholders.
