We are looking for a highly analytical and business-oriented Business Analyst to support data-driven decision making across our D2C and Marketplace business. This role will work closely with Growth, Performance Marketing, CRM, Product, Category, Finance, and Leadership to uncover insights, solve business problems, and identify growth opportunities.

The ideal candidate combines strong analytical capabilities with commercial thinking, has prior experience in a D2C or consumer internet business, and enjoys translating complex data into actionable business recommendations.

Experience:

- 2-4 years of experience in Business Analytics, Growth Analytics, Commercial Analytics, or Strategy.

- Prior experience at a leading D2C, ecommerce, consumer internet, or marketplace company is mandatory.

- Experience working with cross-functional teams including Marketing, Product, Category, CRM, Finance, and Technology.

- Demonstrated ability to influence business decisions using data.

Educational Qualifications:

- Bachelor's degree in Engineering, Mathematics, Statistics, Economics, Computer Science, Business, or a related quantitative discipline.

- Candidates from Tier 1 institutes preferred or Other premier Indian or global institutions.

Key Responsibilities:

1. Business Analytics:

- Analyze business performance across customer acquisition, retention, revenue, profitability, merchandising, and operations.

- Identify growth opportunities, risks, and performance bottlenecks.

- Translate business problems into structured analytical frameworks and actionable recommendations.

- Support leadership in strategic decision-making through data-driven insights.

2. Dashboarding & Reporting:

- Build and maintain automated dashboards for key business metrics.

- Monitor daily, weekly, and monthly performance across business functions.

- Ensure accuracy, consistency, and reliability of reporting.

- Develop executive-ready reports and business reviews.

3. Growth & Marketing Analytics:

Partner with Growth and Marketing teams to analyze:

- Marketing efficiency

- Customer Acquisition Cost (CAC)

- Return on Ad Spend (ROAS)

- Marketing Efficiency Ratio (MER)

- Funnel conversion

- Channel performance

- Customer cohorts

- Incrementality of campaigns

- New vs Repeat customer performance

4. Customer & Retention Analytics:

Support CRM and Retention teams by analyzing:

- Customer Lifetime Value (LTV)

- Repeat Purchase Rate

- Churn

- Customer segmentation

- Cohort behavior

- RFM analysis

- Campaign effectiveness

- Loyalty program performance

5. Product & Ecommerce Analytics:

Analyze the end-to-end ecommerce funnel, including:

- Homepage performance

- Search behavior

- Product Listing Page (PLP) performance

- Product Detail Page (PDP) conversion

- Add-to-Cart rate

- Checkout funnel

- Payment success rate

- Order conversion

- AOV

- Revenue per visitor

- Identify opportunities to improve conversion and customer experience.

6. Category & Commercial Analytics:

Support Category teams with:

- SKU performance

- Category profitability

- Pricing analysis

- Inventory health

- Assortment optimization

- Product affinity analysis

- Demand forecasting

- Sell-through analysis

7. Experimentation:

- Design and evaluate A/B tests across Product, Marketing, CRM, and Ecommerce.

- Measure incremental impact of experiments.

- Build frameworks for experimentation and hypothesis testing.

- Recommend next steps based on statistical and business significance.

8. Forecasting & Business Planning:

- Support monthly and quarterly business planning.

- Build forecasting models for revenue, traffic, orders, and customer growth.

- Identify leading indicators and business risks.

- Track actual performance against forecasts.

9. Success Metrics:

The role will be measured on:

- Accuracy and reliability of reporting

- Speed of insight generation

- Business impact of recommendations

- Dashboard adoption by stakeholders

- Forecast accuracy

- Experimentation support

- Quality of business analyses

- Stakeholder satisfaction

- Automation of reporting processes

Desired Skills:

- Advanced SQL (mandatory)

- Advanced Microsoft Excel / Google Sheets

- Python or R for data analysis (preferred)

- Experience with BI tools such as Power BI, Tableau, Looker, or Metabase

- Strong understanding of statistics and hypothesis testing

- Excellent problem-solving and structured thinking

- Ability to simplify complex datasets into actionable insights

- Strong communication and presentation skills

- High attention to detail and data accuracy

Preferred Experience:

- Candidates from leading D2C, ecommerce, consumer internet, or marketplace companies.

The successful candidate will have:

- Strong business acumen with the ability to connect data to commercial outcomes.

- A structured and hypothesis-driven approach to problem-solving.

- Curiosity to identify trends, anomalies, and opportunities proactively.

- Excellent stakeholder management and the confidence to challenge assumptions with data.

- A bias for automation, efficiency, and continuous improvement.

- Strong ownership, attention to detail, and the ability to work in a fast-paced, high-growth environment.