Purpose & Overall Relevance for the Organization
The Retail Analyst supports Retail and Franchise performance by transforming data into clear insights that improve commercial outcomes, operational efficiency, and product productivity.
The role is responsible for building dashboards, managing retail datasets, and analysing store results across sales, KPIs, stock health, and product performance, enabling teams to make faster and more informed decisions.
A strong understanding of fashion retail fundamentals, retail math, and buying/merchandising ratios is essential.
Key Responsibilities
- Retail Reporting & Dashboard Management
- Build, enhance, and maintain retail dashboards using Power BI covering sales, traffic, conversion, UPT, ATV, stock availability, sell-through, and shrinkage.
- Ensure reporting accuracy and alignment across Retail, Merchandising, and Finance teams.
- Prepare regular and ad-hoc reports for business reviews and leadership meetings.
Store & KPI Analysis
- Analyse store performance and retail KPIs using retail formulas (e.g., sell-through %, WOS, SPH, conversion).
- Evaluate product mix efficiency, category contribution, and merchandising ratios to support buying and allocation decisions.
- Provide insights on staffing productivity, store format differences, and operational execution indicators.
Product, Stock & Merchandising Analytics
- Track product performance by category, gender, concept, and franchise level.
- Support Merchandising with data on size curves, top sellers, ageing inventory, replenishment needs, and size depth analysis.
- Analyse inline and seasonal performance to support OTB discussions and assortment planning inputs (without owning OTB).
Data Modelling & BI Development
- Build data models and queries to support scalable reporting in Power BI.
- Collaborate with IT/Data teams to improve data pipelines, database integrity, and automation.
- Maintain clean and consistent datasets, ensuring reliable foundations for all reporting.
Cross-Functional Support & Collaboration
- Partner with Retail Ops, Merchandising, VM, Finance, and eCommerce to align on insights and ensure data-driven execution.
- Provide analytical support for retail initiatives, productivity improvement workstreams, and store performance deep dives.
- Support leadership presentations and business narratives with clear, visual data storytelling.
Key Relationships
Internal: Retail Operations, Buying, Data & Analysis Teams, & Finance
Technical Skills
Knowledge, Skills & Abilities
- Proficiency in Power BI (DAX, data modelling, dashboard design).
- Advanced Excel; familiarity with SQL, Advanced Python / R + libraries & Vega / VegaLite is advantageous.
- Strong data cleaning, structuring, and visualization capability.
Retail Knowledge
- Solid understanding of fashion retail fundamentals and retail math:
- Sell-through, WOS, productivity metrics
- Buying & merch ratios (gender/category splits, A/B/C classifications, size curves, price points)
- Conversion KPIs, operational KPIs, product lifecycle
- Ability to interpret store data and translate it into commercial insights.
Core Competencies
- High attention to detail and accuracy.
- Strong analytical thinking and ability to simplify complex data.
- Good communication and collaboration skills.
- Organized; able to manage multiple datasets and reporting deadlines.
- Curious, proactive, and eager to learn retail systems and processes.
Requisite Education & Experience / Minimum Qualifications
- 04 years of experience in retail analytics, commercial analysis, or data analytics roles.
- Fresh graduates with strong Power BI skills and understanding of retail KPIs are welcome.
- Degree in Business, Data Analytics, Economics, Statistics, Computer Science, or related fields.
- Experience in fashion, sporting goods, or FMCG retail is an advantage.
adidas celebrates diversity, supports inclusiveness and encourages individual expression in our workplace. We do not tolerate the harassment or discrimination toward any of our applicants or employees. We are an equal opportunity employer.
