Rentomojo Data Analyst Interview: Rounds, Questions and Preparation

What the job involves

As a Data Analyst at an Indian unicorn or high-growth startup like Rentomojo, you will spend your day pulling data from multiple sources, cleaning it, and building dashboards that help teams track rental conversions, customer churn, and inventory utilization. You will also run ad-hoc analyses for product, marketing, and operations teams, and present findings in simple language to non-technical stakeholders. Expect a fast pace where your insights directly influence pricing, retention campaigns, and supply chain decisions.

Role and sector knowledge

1. 1

   What does a typical day look like for a data analyst at a rental or subscription-based startup?

   Mention pulling rental order data, tracking active subscriptions, building daily dashboards for operations, and answering ad-hoc queries about customer lifetime value or return rates.

2. 2

   How would you measure the success of a furniture rental company like Rentomojo?

   Focus on metrics such as monthly recurring revenue, average rental duration, customer acquisition cost, churn rate, and inventory turnover. Show you understand the rental model vs one-time sales.

3. 3

   Why do high-growth startups need data analysts more than large established firms?

   Explain that startups pivot quickly, run many experiments, and need fast, data-backed decisions on pricing, marketing spend, and product features without large legacy reporting teams.

4. 4

   What are the key differences between analyzing data for an e-commerce company versus a rental startup?

   Highlight that rentals involve recurring revenue, asset tracking, return logistics, and depreciation, while e-commerce focuses on one-time purchases, cart abandonment, and delivery speed.

Technical skills and tools

1. 5

   Write a SQL query to find the top 5 cities by number of active rentals in the last 30 days.

   Use a WHERE clause for date filtering, GROUP BY city, COUNT of rental IDs, ORDER BY count DESC, and LIMIT 5. Explain how you handle missing city values.

2. 6

   How would you use Excel or Google Sheets to clean a list of 10,000 customer records with duplicate phone numbers and missing emails?

   Mention remove duplicates, conditional formatting to spot blanks, TRIM and PROPER for text, and using COUNTIF to flag duplicates before deciding on a merge or deletion rule.

3. 7

   What is the difference between a LEFT JOIN and an INNER JOIN, and when would you use each in a rental database?

   Explain that LEFT JOIN keeps all customers even if they have no rentals, useful for churn analysis, while INNER JOIN only shows customers with at least one rental, useful for active user reports.

4. 8

   Given a table of rental transactions with columns customer_id, product_id, start_date, end_date, and monthly_fee, how would you calculate average rental duration per product category?

   Use DATEDIFF or date subtraction to get duration, join to a product category table, then GROUP BY category and AVG the duration. Mention handling null end_date for ongoing rentals.

Practical scenarios and case study

1. 9

   Rentomojo sees a 15% drop in new rentals in one city last month. How would you investigate the cause?

   Break down by traffic source, product category, pricing changes, competitor activity, and seasonality. Suggest checking marketing spend, app crash reports, and customer support tickets for that city.

2. 10

   You are asked to design a dashboard for the operations team to track furniture return condition and repair costs. What metrics and charts would you include?

   Include return rate by product, average repair cost per item, days in repair, and top damaged categories. Suggest a line chart for trends and a bar chart for cost by category.

3. 11

   The marketing team wants to know if a new email campaign increased subscription upgrades. How would you set up and analyze an A/B test?

   Define control and test groups, choose a primary metric like upgrade rate, run for a fixed period, and use a two-proportion z-test. Mention checking for sample size and avoiding peeking early.

4. 12

   You find that 20% of rental orders have missing delivery dates. How would you handle this before building a monthly report?

   First quantify the missingness, check if it is random or tied to a specific city or product, then decide to exclude, impute with median, or flag as incomplete. Always document the decision.

Behavioural and HR questions

1. 13

   Tell me about a time you used data to solve a problem in a college project or internship.

   Use the STAR method: describe the dataset, the question, the tool you used, and the concrete outcome. Emphasize what you learned about cleaning or presenting data.

2. 14

   Why do you want to work at a high-growth startup like Rentomojo instead of a large IT services company?

   Show that you value ownership, fast learning, and seeing your analysis directly impact business decisions. Mention specific startup traits like cross-functional teamwork and rapid iteration.

3. 15

   Describe a situation where you had to explain a technical finding to a non-technical person.

   Pick an example from a group project or presentation. Explain how you avoided jargon, used simple charts, and checked for understanding. Highlight the positive outcome.

4. 16

   How do you handle tight deadlines when multiple teams ask for data at the same time?

   Talk about prioritizing based on business impact, communicating trade-offs, and using reusable queries or templates. Show you are organized and calm under pressure.