Senior Data Scientist - Neural Net Forecasting in Welwyn

About Us

Hackajob is collaborating with Tesco to connect them with exceptional professionals for this role. Our vision at Tesco is to become every customer's favourite way to shop, whether they are at home or out on the move. Our core purpose is ‘Serving our customers, communities and planet a little better every day’. Serving means more than a transactional relationship with our customers. It means acting as a responsible and sustainable business for all stakeholders, for the communities we are part of and for the planet. We are proud to have an inclusive culture at Tesco where everyone truly feels able to be themselves. At Tesco, we not only celebrate diversity, but recognise the value and opportunity it brings. We’re committed to creating a workplace where differences are valued, and make sure that all colleagues are given the same opportunities. We’re proud to have been accredited Disability Confident Leader and we’re committed to providing a fully inclusive and accessible recruitment process. For further information on the accessibility support we can offer, please see our accessibility page. We’re a big business and we can offer a range of diverse full‑time & part‑time working patterns across our many business areas, which means that we can find something that works for you. We work in a more blended pattern – combining office and remote working. Our offices will continue to be where we connect, collaborate and innovate. If you are applying internally, please speak to the Hiring Manager about how this can work for you – Everyone is welcome at Tesco.

About The Role

At Tesco, our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work extends across multiple areas including physical stores, online, finance, and supply chain. The Data Science team works across several domains and problem types: forecasting, online, pricing, security, fulfilment, distribution, property, IoT and computer vision are just some. Our 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. Furthermore, we offer a great work‑life balance, regular team days and a relaxed yet engaging culture.

Responsibilities

• 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 CV, 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.

Qualifications

We are looking for ambitious individuals with a mix of statistics, programming skills and familiarity with time series analysis. A proven track record of designing and modifying advanced algorithms and applying them to large data sets is essential. Some project and stakeholder management experience is preferred. An ideal candidate will have a scientific mindset with the ability to ask the right questions, as well as answer them. A strong numerical higher degree in a mathematical, scientific, engineering or computer science discipline is preferable, as well as 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. This includes experience with neural network architectures for forecasting (for example 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. Finally, strong programming skills are essential (Python is preferred) as well as familiarity with software engineering best practices (such as version control, unit testing, CI/CD) and big data and cloud technologies (PySpark preferred). Experience training and deploying deep learning models in cloud environments (including GPU‑enabled workflows) is a strong advantage.

Benefits

• 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 or adoption pay, and 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.
• This information is a shortened summary, refer to our policies for full details.