Space Planning Analyst — Remote & Data-Driven Growth

Tesco UK; Greater London; Hybrid; GBP 30,000 - 50,000; Full time

Job summary

The role requires a quantitative degree and experience in analytics or merchandising; proficiency with Excel, SQL, Python, and R is desirable. You will work in a hybrid setup with collaboration across Store Ordering, Merchandising and Property teams.

Qualifications

• Degree in a quantitative or retail subject is required.
• Experience in retail analytics or merchandising is desirable.
• Familiarity with data manipulation, analytical tools (MS Excel, SQL, Python, R, VBA) is a plus.
• Strong numerical and analytical skills with the ability to communicate insight clearly.

Responsibilities

• Support the Trade Planning Team to identify and deliver growth opportunities in seasonal events and promotions space through clear reporting.
• Build robust event cascades accounting for space constraints, phasing, and country dynamics.
• Interface with store space database to align store lists with event space.
• Design and deliver timely analysis for space data, sales, density and volume performance.
• Develop decision-led reporting for space modelling, optimisation and allocation to support Event Manager decisions.
• Issue accurate data to SRM and Supply Chain partners ensuring space plans reflect event execution.
• Identify, diagnose and resolve complex data issues for robust analysis.
• Support end-to-end process from planning and forecasting through post-event review.
• Proactively identify opportunities to standardise and automate processes.
• Collaborate with Event Managers and Space, Range, Merchandising, Store Ordering and Property teams to align plans and space.
• Oversee loading, extraction and transformation of large datasets from the data warehouse.
• Conduct ad hoc research to diagnose performance trends and issues.

Skills

Analytical thinking

SQL

Python

Excel

Data visualization

Education

Degree in quantitative or retail subject

Tools

SQL

Python

R

VBA

Job description

The role requires a quantitative degree and experience in analytics or merchandising; proficiency with Excel, SQL, Python, and R is desirable. You will work in a hybrid setup with collaboration across Store Ordering, Merchandising and Property teams.