Mosaic Wellness Data Analyst Interview: Rounds, Questions and Preparation

What the job involves

As a Data Analyst at an Indian unicorn or high-growth startup like Mosaic Wellness, you will work with product, marketing, and operations teams to track business health, run experiments, and turn raw data into decisions. Day to day you will write SQL, build dashboards, analyse funnels and cohorts, and present insights to non-technical stakeholders in fast weekly cycles.

Role and Technical Knowledge

1. 1

   How would you write a SQL query to find the top 5 cities by number of new users in the last 30 days?

   Mention filtering by date, grouping by city, counting distinct users, ordering descending, and limiting to 5. Show awareness of date functions and handling null cities.

2. 2

   What is the difference between a left join and an inner join, and when would you use each in a customer orders table?

   Explain that inner join keeps only matching rows while left join keeps all rows from the left table. Give an example like finding customers with no orders using a left join and null check.

3. 3

   How would you calculate month-over-month retention for a subscription wellness product?

   Define a cohort by first purchase month, then track whether the same users transact in later months. Discuss retention rate formula and why cohort analysis beats overall averages.

4. 4

   What steps would you take to clean a messy marketing dataset with duplicate rows and missing spend values?

   Cover removing duplicates, deciding whether to drop or impute missing values, checking date formats, and documenting assumptions. Mention using pandas or spreadsheets and validating with summary stats.

Practical Scenarios

1. 5

   Daily active users dropped 15 percent week over week. How would you investigate this as a data analyst?

   Start by validating the data pipeline, then segment by platform, geography, and acquisition channel. Check for tracking bugs, seasonality, and recent product or marketing changes before concluding.

2. 6

   The marketing team wants to know which channel gives the best return. What data would you pull and how would you present it?

   Mention CAC, conversion rate, and LTV by channel, plus time lag between spend and conversion. Suggest a simple dashboard with clear recommendations, not just numbers.

3. 7

   A product manager asks you to measure the success of a new onboarding flow. What metrics and method would you use?

   Propose an A/B test with a clear primary metric like activation rate and guardrail metrics like support tickets. Discuss sample size, test duration, and checking for statistical significance.

4. 8

   You find that a dashboard shows revenue higher than the finance team's numbers. How do you handle it?

   Show ownership by checking definitions, filters, time zones, and refund handling. Communicate calmly with both teams, align on a single source of truth, and document the fix.

Behavioural and HR

1. 9

   Why do you want to work as a data analyst at a fast-growing startup instead of a large established company?

   Show comfort with ambiguity, broad ownership, and quick iteration. Connect your interest to learning across product, marketing, and operations in a high-growth environment.

2. 10

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

   Use a simple STAR structure: situation, task, action, result. Highlight the dataset, the method, and the decision or outcome your analysis supported.

3. 11

   Describe a time you had to explain a technical finding to someone non-technical.

   Focus on simplifying without losing accuracy, using visuals or analogies, and checking understanding. Show that you value the business decision over the technical detail.

4. 12

   How do you handle feedback when a senior stakeholder disagrees with your analysis?

   Show openness, ask clarifying questions, and revisit assumptions with data. Emphasise that the goal is the right decision, not being right personally.

Domain and Startup Context

1. 13

   What metrics would you track for a direct-to-consumer wellness brand?

   Mention CAC, repeat purchase rate, LTV, average order value, churn, and subscription retention. Show awareness that wellness brands often rely on repeat purchases and community.

2. 14

   How would you analyse the impact of a festive sale on customer behaviour?

   Compare pre-sale, during-sale, and post-sale cohorts for new versus returning customers. Look at discount depth, basket size, and whether new buyers return after the sale.

3. 15

   What is one data quality issue common in Indian startup environments and how would you address it?

   Examples include inconsistent city names, mixed date formats, or duplicate user IDs across apps. Suggest standardisation rules, validation checks at entry, and periodic audits.

4. 16

   How would you decide which experiment to run first when the team has limited engineering bandwidth?

   Prioritise by expected impact, confidence, and effort. Suggest a simple scoring framework and align with business goals like retention or revenue.