Fyers Data Analyst Interview: Rounds, Questions and Preparation

What the job involves

Data Analysts at Indian unicorns and high-growth startups like Fyers work on live product and business data to drive decisions. They write SQL and Python to extract and clean data, build dashboards, run experiments, and present insights to product, marketing, and operations teams. The pace is fast, with short feedback loops and a strong focus on measurable business impact.

Role and Technical Knowledge

1. 1

   How would you write a SQL query to find the second highest trading volume for a stock on a given day?

   Use a subquery with MAX or a window function like DENSE_RANK. Mention handling ties and NULLs.

2. 2

   Explain the difference between a JOIN and a UNION in SQL. When would you use each?

   JOIN combines columns from related tables; UNION stacks rows from similar tables. Give a practical example from user and transaction data.

3. 3

   What is A/B testing, and how would you check if a new feature increased user engagement for a trading app?

   Define null and alternative hypotheses, choose a metric like daily active users or trade count, run a t-test, and check p-value and practical significance.

4. 4

   How do you handle missing or outlier values in a dataset of user trades before analysis?

   Discuss imputation, removal, or flagging based on context. Mention using IQR or z-score for outliers and documenting decisions.

Practical Scenarios

1. 5

   You are given a week of user sign-up and first-trade data. How would you identify where the onboarding funnel drops off?

   Map the funnel steps (sign-up, KYC, first deposit, first trade), calculate conversion at each step, and segment by acquisition channel or device.

2. 6

   A product manager asks you to find why daily active users dropped 10 percent last Tuesday. What do you do?

   Check for data pipeline issues, seasonality, app releases, and external events. Break down by platform, region, and user cohort to isolate the cause.

3. 7

   You need to build a dashboard for the marketing team to track campaign performance. What metrics would you include and why?

   Include CAC, ROAS, conversion rate, and retention by campaign. Explain how each metric ties to spend efficiency and user quality.

4. 8

   How would you estimate the lifetime value (LTV) of a new user for a subscription-based fintech product?

   Use average revenue per user, gross margin, and churn rate. Mention cohort analysis and simplifying assumptions for a quick estimate.

Problem Solving and Data Interpretation

1. 9

   Given a table of user sessions with timestamps, how would you calculate the average session duration per user?

   Use window functions to find session start and end, then average the difference. Handle sessions that span midnight or have gaps.

2. 10

   You find that users who trade more than 10 times a month have higher retention. Does that mean trading causes retention?

   Explain correlation vs causation. Suggest an experiment or propensity score matching to test causality.

3. 11

   How would you detect and handle duplicate transactions in a payments dataset?

   Define duplicates using transaction ID, user ID, amount, and timestamp. Use GROUP BY and HAVING to find them, then decide on deduplication rules.

4. 12

   A stakeholder wants a report by end of day but the data is incomplete. How do you proceed?

   Communicate data limitations clearly, provide preliminary insights with caveats, and set expectations for a final update.

Behavioural and HR

1. 13

   Why do you want to work as a data analyst at a high-growth startup like Fyers instead of a large established company?

   Show comfort with ambiguity, ownership, and fast iteration. Mention specific interest in fintech or trading data.

2. 14

   Tell me about a time you used data to convince someone to change their decision.

   Use the STAR method. Focus on how you presented the data, handled pushback, and measured the outcome.

3. 15

   Describe a project where you had to learn a new tool or technique quickly. How did you manage?

   Highlight self-learning, time management, and applying the new skill to deliver a result. Mention any online courses or documentation used.

4. 16

   How do you prioritize multiple data requests from different teams?

   Discuss impact vs effort, clarifying deadlines, and communicating trade-offs. Give an example of saying no or negotiating scope.