Data Scientist – Neural Net Forecasting

Overview

At Tesco, our Data Science team focuses on modelling complex business problems and deploying data products  work extends across multiple areas including physical stores, online, finance, and supply chain. The team works across several domains and problem types: forecasting, online, pricing, security, fulfilment, distribution, property, IoT and computer vision are just some. Team members are encouraged to allocate working hours for learning and personal development every week and are provided with multiple learning resources and tools.

Multiple academic collaborations enrich the team’s expertise; knowledge‑sharing events are held regularly. We offer a great work‑life balance, regular team days and a relaxed yet engaging culture.

We are committed to a fully inclusive and accessible recruitment process. We are proud to be accredited Disability Confident Leader and recognize that diversity creates value. All colleagues are given the same opportunities.

This is a hands‑on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Data Scientist, you will need to understand difficult business problems and prototype solutions with minimal support. Your responsibilities include:

• Design and improve deep learning and related machine learning forecasting models for large‑scale retail time series.
• Build robust training and back‑testing pipelines (time‑aware cross‑validation, leakage controls, stability checks).
• Apply best practices for productionisation (monitoring, retraining strategies, performance and cost considerations).
• Collaborate closely with engineering, product, and business partners to ensure models are reliable, scalable, and deliver measurable business value.
• Validate, document and present the modelling process and performance, and communicate complex solutions in a clear, understandable way to non‑experts.
• Promote data science across Tesco and represent Tesco in the external Data Science community.
• Drive innovation, take ownership of aspects of project development, support the Lead Data Scientist and Product Manager in managing relationships with business stakeholders, and mentor and supervise junior team members and interns.

• Strong programming skills in Python (preferred). Familiarity with software engineering best practices such as version control, unit testing, CI/CD.
• Experience with big data and cloud technologies, PySpark preferred.
• A proven track record of designing and modifying advanced algorithms and applying them to large data sets.
• Some project and stakeholder management experience is preferred.
• Scientific mindset with the ability to ask and answer the right questions.
• Strong numerical higher degree in a mathematical, scientific, engineering or computer science discipline, and a solid understanding of mathematics and statistical principles.
• Meaningful academic or industrial work involving deep learning or related machine learning techniques for time series forecasting is required.
• Experience with neural network architectures for forecasting (sequence models, temporal convolutional approaches, transformer‑style models, or related methods).
• Experience with probabilistic forecasting, hierarchical forecasting, or representation learning for time series is a plus.
• Experience training and deploying deep learning models in cloud environments (including GPU‑enabled workflows) is a strong advantage.

• 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; 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.