Retail Data & Analytics Analyst — AI-Driven Insights

Sainsbury's Limited; Greater London; Hybrid; GBP 43,000 - 65,000; Full time

Benefits offered by this job

Colleague discount

Pensions & life cover

Performance bonus up to 10%

Holiday allowance

Season ticket loans

Cycle to work

Health cash plans

Salary advance

Employee assistance programme

Maternity/paternity leave

Job summary

Sainsbury's Limited is seeking an Analyst within Retail Transformation Analytics to deliver analytics projects from problem understanding to insight and recommendations. You'll work with stakeholders, translate challenges into analytical questions, and use SQL and Python to explore large datasets.

You'll turn findings into practical recommendations, communicate clearly through data visualisation and storytelling, and ensure data quality and robust assumptions.

Qualifications

• Demonstrable strong experience using SQL to query, combine and analyse large or complex datasets.
• Demonstrable experience using Python for data manipulation, analysis and visualisation.
• Practical experience applying analytical or statistical modelling techniques (e.g., regression, classification, forecasting).
• Knowledge of distributions, sampling, statistical significance, correlation and uncertainty.

Responsibilities

• Deliver analytics projects from problem understanding to insight and recommendation.
• Work with stakeholders across Retail Transformation to translate challenges into analytical questions.
• Use SQL and Python to explore large, complex datasets and communicate findings clearly through visualization.

Skills

SQL

Python

Statistical modelling

Statistical concepts

Business problem translation

Job description

Sainsbury's Limited is seeking an Analyst within Retail Transformation Analytics to deliver analytics projects from problem understanding to insight and recommendations. You'll work with stakeholders, translate challenges into analytical questions, and use SQL and Python to explore large datasets.

You'll turn findings into practical recommendations, communicate clearly through data visualisation and storytelling, and ensure data quality and robust assumptions.