At Tesco, our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores, online, supply chain, marketing and Clubcard, where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects.
We work on several domains and problem types: online, pricing, security, fulfilment, distribution, property, IoT and computer vision are just some. Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge-sharing events are regular. Furthermore, we have got a great work-life balance, team days and relaxed but engaging culture.
This is a hands-on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Senior Data Scientist, you will need to understand difficult business problems and prototype solutions with minimal support. Apply, modify and design metaheuristic algorithms and mathematical models to solve business problems is a core component of the role. Our data scientists will need to be able to validate, document and present the solution approaches and performances, as well as communicate complex solutions in a clear, understandable way to non-experts. Data Scientists are also responsible for promoting data science across Tesco and promote Tesco across the external Data Science community. Finally, as a Senior Data Scientist, you will be expected to drive innovation and take ownership of aspects of the project development, help the Principal and Lead Scientists and the Product Managers manage the relationships with the business stakeholders and mentor/supervise junior members of the team and/or interns.
We are looking for ambitious individuals with a mix of mathematical optimisation, programming and statistics skills. The role requires that you have an extensive background in Operational Research and metaheuristic domain. A track record in designing and modifying advanced heuristic and metaheuristic algorithms and applying those to large-scale real-world problems. Project and stakeholder management experience is preferred.
You should be able to demonstrate a deep knowledge of state-of-the-art approaches and algorithms in combinatorial optimisation. You should be enthused to apply these techniques in a commercial or industrial setting, and encourage collaboration and communication between teams. An ideal candidate will have a scientific mentality with the ability to ask the right questions, as well as answer them.
A year or more of post-doctoral research in an area of operational research or similar equivalent industrial experience is preferable, as well as a solid understanding of mathematics and statistical principles. Finally, strong programming skills are essential (Java and Python are preferred) as well as familiarity with software engineering best practices (such as version control, OOP, unit testing, CI/CD) and cloud technologies.