Senior Data Scientist - Neural Net Forecasting

Salary: £36,000 - 76,000 per year

Requirements:

• 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.
• Experience with neural network architectures for forecasting, such as sequence models, temporal convolutional approaches, transformer-style models, or related methods, is required.
• Experience with probabilistic forecasting, hierarchical forecasting, or representation learning for time series is a plus.
• Strong programming skills are essential, with Python preferred.
• Familiarity with software engineering best practices such as version control, unit testing and CI/CD is required.
• Familiarity with big data and cloud technologies, with PySpark preferred, is required.
• Experience training and deploying deep learning models in cloud environments, including GPU-enabled workflows, is a strong advantage.

Responsibilities:

• Use an analytical mindset to solve complex business problems.
• Understand difficult business problems and prototype solutions with minimal support.
• Apply, modify and design algorithms and mathematical models to solve business problems using big data architectures such as Hadoop, Spark and Cloud.
• Focus on neural network-based forecasting, with rigorous evaluation against robust baselines, careful validation and scalable deployment.
• Validate, document and present the modelling process and performance.
• Communicate complex solutions clearly and understandably to non-experts.
• Promote data science across Tesco and represent Tesco within the external Data Science community.
• Drive innovation and take ownership of aspects of project development.
• Support the Lead Data Scientist and Product Manager in managing relationships with business stakeholders.
• Mentor and supervise junior team members and interns.
• Design and improve deep learning and related machine learning forecasting models for large-scale retail time series.
• Build robust training and backtesting pipelines, including time-aware cross-validation, leakage controls and stability checks.
• Apply best practices for productionisation, including 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.

Technologies:

• Big Data
• CI/CD
• Cloud
• Computer Vision
• Hadoop
• IoT
• Support
• Machine Learning
• Network
• Product Manager
• Python
• PySpark
• Security
• Spark

More:

We are Tesco, and our Data Science team focuses on modelling complex business problems and deploying data products at scale across physical stores, online, finance and supply chain. Our team works across forecasting, online, pricing, security, fulfilment, distribution, property, IoT and computer vision, and we support learning and personal development every week with multiple resources and tools. We also benefit from academic collaborations, regular knowledge-sharing events, a great work-life balance, regular team days and a relaxed yet engaging culture. Our colleague benefits package includes an annual bonus scheme of up to 20% of base salary, holiday starting at 25 days plus a personal day and Bank holidays, private medical insurance, maternity, adoption and paternity leave, and free virtual GP and employee wellbeing support. We have an inclusive culture, a blended working pattern combining office and remote working, and a range of full-time and part-time working patterns across our business.

last updated 39 week of 2026