As a Data Analyst, you'll be at the core of decision-making by analyzing category-level data, understanding consumer preferences, and enabling data-driven strategies for curation and assortment. You'll work cross-functionally with Category Managers, Growth Marketing, and Operations teams to ensure that we offer the right SKUs, at the right time, for the right audience.

Key Responsibilities

Category Performance Analysis

- Analyze sales, inventory, and category performance to identify trends, gaps, and opportunities.

- Provide actionable insights to optimize SKU selection, pricing, and promotions.

Consumer Behavior Insights

- Conduct deep dives into customer data to understand preferences, buying patterns, and regional variations.

- Develop user segmentation models to tailor category strategies effectively.

Assortment and Demand Forecasting

- Collaborate with Category Managers to forecast demand, optimize inventory levels, and reduce stockouts.

- Leverage predictive models to suggest category expansions and reduce churn.

Competitive Benchmarking

- Conduct market analysis to benchmark FirstClub's offerings against competitors in the premium and quick commerce segments.

- Identify emerging product trends and gaps in the market.

Data-Driven Merchandising

- Work with Category Managers and Merchandising Teams to refine product placement and presentation based on data insights.

- Suggest SKU introductions or removals based on user behavior and sales patterns.

Dashboard and Reporting

- Build and maintain dynamic dashboards and reports for real-time tracking of category performance.

- Create data visualizations that empower stakeholders to make informed decisions.

Collaboration and Stakeholder Management

- Partner closely with Growth Marketing, Operations, and Tech Teams to align category goals with overall business objectives.

- Provide regular updates and insights to senior management on category performance.

Who You Are

- Analytical and Insightful: You have a knack for identifying patterns in large data sets and translating them into actionable business insights.

- Detail-Oriented Problem Solver: You enjoy solving complex problems and know how to balance data accuracy with speed.

- Proactive and Collaborative: You work well with cross-functional teams and have a bias toward action.

- Tech-Savvy with Tools: You are comfortable with SQL, Python/R, and visualization tools such as Tableau or Power BI.

- E-Commerce and Retail Enthusiast: You have a solid understanding of e-commerce, category management, and consumer behavior.

Skills and Qualifications

- Education: Bachelor's or Master's degree in Data Science, Statistics, Business Analytics, or a related field.

- Experience: 6 to 8 years of hands-on experience in data analysis, preferably in e-commerce, quick commerce, or retail.

Technical Proficiency:

- Strong expertise in SQL, Excel, and data visualization tools (Tableau/Power BI).

- Working knowledge of Python or R for data analysis is a plus.

Business Acumen:

- Solid understanding of category management and merchandising principles.

- Ability to draw actionable insights from data to drive business growth.