Senior Data Scientist — Time Series Forecasting in the Cloud

Tesco UK; Digswell; Hybrid; GBP 95,000 - 150,000; Full time

Job summary

Tesco Stores Limited is seeking a Senior Data Scientist to lead forecasting and probabilistic modelling for large-scale retail data. You will prototype solutions with minimal support and drive innovation while coordinating with stakeholders across engineering, product and business teams.

The role emphasizes model validation, clear communication of results to non-experts, and scalable deployment in cloud environments. A strong mathematical background and Python proficiency are essential.

Qualifications

• Advanced degree in a quantitative field (e.g., mathematics, statistics, computer science, engineering).
• Strong background in statistics, forecasting, and time-series analysis.
• Proficiency in Python and data science tooling; experience with PySpark and big data stacks.

Responsibilities

• Designing and improving forecasting and statistical modelling solutions for large-scale retail and business time series.
• Blending data from multiple sources to explain historic behaviour and generate forward-looking predictions.
• Building robust training, validation and backtesting pipelines with time-aware evaluation and leakage controls.
• Applying best practices for productionisation, including monitoring, retraining strategies, and cost considerations.
• Collaborating with engineering, product and business partners to deliver reliable, scalable models with measurable business value.

Skills

Statistics

Forecasting

Time series

Python

Big data

Cloud

Spark

Hadoop

CI/CD

Model deployment

Education

Master's or PhD in quantitative field

Tools

PySpark

Spark

Hadoop

Cloud platforms

Git

Job description

Tesco Stores Limited is seeking a Senior Data Scientist to lead forecasting and probabilistic modelling for large-scale retail data. You will prototype solutions with minimal support and drive innovation while coordinating with stakeholders across engineering, product and business teams.

The role emphasizes model validation, clear communication of results to non-experts, and scalable deployment in cloud environments. A strong mathematical background and Python proficiency are essential.