2 of 2 Permanent Data Science Leader Jobs in Worcester

Technical Lead - Data Science & Engineering Hybrid - Two Days a week Competitive salary + benefits About the Role: An exciting opportunity has arisen for a Technical Lead to drive innovation across data science and engineering initiatives within a growing and forward-thinking software provider. You'll play a key role in shaping a … unified data platform and delivering high-impact machine learning and data solutions across cloud and hybrid environments. This is a hands-on leadership role, combining deep technical expertise with mentoring and cross-functional collaboration. What You'll Be Doing: Architect and scale a modern data platform and DaaS (Data-as-a-Service … infrastructure Lead and mentor a team of data scientists and engineers across multiple projects Oversee the deployment and monitoring of machine learning models in production Define coding standards and implement best practices in CI/CD, MLOps, and API delivery Collaborate with business, product, and engineering teams to align data strategy with commercial goals Champion data More ❯

Lead Data Science Engineer Hybrid - 2 days a week Competitive salary + excellent benefits About the Role: A forward-thinking tech company is seeking a Lead Data Science Engineer to join their growing data function. This is a strategic, hands-on role where you'll design and build modern data infrastructure, guide the deployment of machine learning models, and shape the delivery of data-driven products and APIs. You'll lead technical initiatives while working closely with data engineers, scientists, architects, and product stakeholders to ensure real-world impact through data. What You'll Be Doing: Architect and implement scalable pipelines and data systems that power advanced analytics and ML applications Lead the rollout of data products, including APIs and secure data delivery mechanisms for clients and internal use Partner with cross-functional teams to align data solutions with wider business goals Take ownership of productionising ML models and integrating them into operational systems Improve More ❯