Retail Analytics Analyst — SQL & Python

Sainsbury’s Group; City of Westminster; On-site; GBP 52,000 - 68,000; Full time

Benefits offered by this job

Colleague discount 10%–15%

Pensions scheme

Performance-related bonus up to 10%

Flexible working

Annual leave with option to buy extra

Job summary

Sainsbury’s Group is seeking an Analyst to deliver analytics projects from problem framing to insight and recommendation. You will work with Retail Transformation and the wider business, translating challenges into analytical questions and using SQL and Python to explore large datasets.

You will turn findings into practical recommendations, communicate through data visualisation and storytelling, and ensure analysis quality by testing assumptions and addressing uncertainty.

Qualifications

• Strong SQL experience with large datasets.
• Python for data manipulation, analysis and visualization.
• Experience with at least one analytical or statistical modelling technique (regression, classification or forecasting).
• Knowledge of distributions, sampling, significance, correlation and uncertainty in analysis.
• Translate business problems into analytical approaches and deliver actionable insights.

Responsibilities

• Deliver analytics projects from problem framing to insight and recommendation.
• Translate challenges into clear analytical questions for stakeholders.
• Combine data from multiple sources and apply exploratory analysis.
• Develop and evaluate analytical models and measure impact of trials and operational changes.
• Communicate findings through data visualization and storytelling; ensure data quality and test assumptions.

Skills

SQL

Python

Statistical Modeling

Data Visualization

Education

Bachelor's degree in a related field

Tools

Power BI

Tableau

Excel

Job description

Sainsbury’s Group is seeking an Analyst to deliver analytics projects from problem framing to insight and recommendation. You will work with Retail Transformation and the wider business, translating challenges into analytical questions and using SQL and Python to explore large datasets.

You will turn findings into practical recommendations, communicate through data visualisation and storytelling, and ensure analysis quality by testing assumptions and addressing uncertainty.