About the role The Tesco Data Science team are looking for a Simulation Data Scientist to use simulation to help solve challenging problems across the business and our supply chain from supplier to shelf.
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. This requires our Data Scientists to have an advanced understanding of statistics and algorithms. The team itself is made up of researchers and practitioners with varied backgrounds from both academia and the business world.
You will develop and connect simulation models to help Tesco understand, evaluate and improve operations, including supply chain, and assess proposed changes before implementation. Working with experienced colleagues, you will contribute to distributed simulations that bring together models of different processes and systems, developing awareness of relevant interoperability standards and approaches. You will build models at different levels of fidelity, learning to choose the appropriate detail for the business question, available data and computing needs. The role will involve using operational data and scenario experiments to validate models, explore trade-offs and inform decisions. Follow agile delivery methods and contribute to continuous integration and delivery practices, including version control, automated testing and repeatable deployment, to help maintain reliable simulation tools.
The position will be based in our Welwyn Garden City campus. What is in it for you We’re all about the little helps. That’s why we make sure our Tesco colleague benefits package takes care of you – both in and out of work. Click Here to find out more!
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. This requires our Data Scientists to have an advanced understanding of statistics and algorithms. The team itself is made up of researchers and practitioners with varied backgrounds from both academia and the business world.
You will develop and connect simulation models to help Tesco understand, evaluate and improve operations, including supply chain, and assess proposed changes before implementation. Working with experienced colleagues, you will contribute to distributed simulations that bring together models of different processes and systems, developing awareness of relevant interoperability standards and approaches. You will build models at different levels of fidelity, learning to choose the appropriate detail for the business question, available data and computing needs. The role will involve using operational data and scenario experiments to validate models, explore trade-offs and inform decisions. Follow agile delivery methods and contribute to continuous integration and delivery practices, including version control, automated testing and repeatable deployment, to help maintain reliable simulation tools.
The position will be based in our Welwyn Garden City campus. What is in it for you We’re all about the little helps. That’s why we make sure our Tesco colleague benefits package takes care of you – both in and out of work. Click Here to find out more!
- Annual bonus scheme of up to 20% of base salary.
- Holiday starting at 25 days plus a personal day (plus Bank holidays).
- Private medical insurance.
- 26 weeks maternity and adoption leave (12 months service required at the qualifying date) at full pay, followed by 13 weeks of Statutory Maternity Pay or Statutory Adoption Pay, we also offer 6 weeks fully paid paternity leave.
- Free 24/7 virtual GP service, Employee Assistance Programme (EAP) for you and your family, free access to a range of experts to support your mental wellbeing.
- Working with colleagues to understand operational problems and agree what a simulation needs to represent, test and measure.
- Building and maintaining simulation models using Python and relevant tools, drawing on simulation and data science skills.
- Creating models at different levels of detail, with guidance on choosing an approach that balances accuracy, available data and computing needs.
- Helping connect models so they can run together and exchange information, including across different tools or computers in distributed or federated simulation environments.
- Developing awareness of the standards and approaches used to connect simulations and applying them with support from experienced colleagues.
- Preparing and analysing operational data to set up models, identify gaps and represent real-world variation.
- Checking that models work as intended and comparing their results with real-world data and feedback from operational experts.
- Running repeatable experiments to assess proposed operational changes, including supply chain scenarios, and compare effects on capacity, cost, service and resource use.
- Explaining findings clearly, including the assumptions made, uncertainty in results and limitations of the models.
- Working in an agile team to plan and deliver tasks in manageable steps, respond to feedback and raise issues early.
- Writing clear, maintainable code and contributing to code reviews, version control, automated testing and reliable software releases.
- Taking responsibility for agreed tasks, asking for support when needed and developing technical skills.
- Python programming, with the ability to write clear, structured and testable code.
- Simulation modelling and an understanding of how to represent real-world processes at different levels of detail.
- Data analysis and basic statistics to prepare model inputs, understand variation and interpret results.
- An understanding of how separate models or software components can exchange data and work together.
- Familiarity with version control, such as Git, and an awareness of automated testing and software delivery practices.
- The ability to explain technical work clearly, document assumptions and work collaboratively.
- An organised approach to solving problems, learning new methods and delivering tasks in an agile team.
- Building or adapting simulation models, or using object oriented programming and data science methods to investigate real-world problems.
- Working with data to develop, test or evaluate models and communicate findings.
- A background in a quantitative subject, such as engineering, computer science, mathematics, physics, operational research, or equivalent practical experience.
- Experience connecting simulations or working in distributed or federated environments would be particularly valuable.
- Exposure to simulation interoperability standards, models with different levels of detail, or automated testing and deployment would be useful but is not essential.