MetLife India Data Consultant Interview: Rounds, Questions and Preparation

What the job involves

A Data Consultant in GCCs, consulting firms and Big 4 setups works with client or internal teams to turn raw data into business decisions, often building dashboards, cleaning datasets and translating findings into clear recommendations. The role sits between business stakeholders and technical teams, so you need comfort with SQL, Excel, one BI tool and basic statistics, plus the ability to explain your work simply. In an established GCC like MetLife India, you may support insurance, risk or operations analytics for global markets, working in structured project cycles with strong documentation and compliance expectations.

Role and domain knowledge

1. 1

   What does a data consultant actually do differently from a data analyst or a data scientist?

   A strong answer separates consulting as client-facing problem framing and recommendations, analyst as reporting and querying, and scientist as modelling and experimentation. Mention that consultants spend a lot of time on stakeholder alignment and storytelling, not only code.

2. 2

   How would you explain the difference between a KPI and a metric to a business stakeholder in an insurance GCC?

   Define a metric as any measurable value, and a KPI as a metric tied directly to a strategic goal, such as claims settlement time or persistency ratio. Give one insurance example and explain why not every metric deserves KPI status.

3. 3

   What are some common data quality issues you expect in insurance or BFSI datasets, and how would you handle them?

   Mention missing policy IDs, duplicate customer records, inconsistent date formats, outliers in claim amounts, and manual entry errors. Explain a practical approach: profile the data, document issues, apply rules with business sign-off, and keep an audit trail.

4. 4

   Why is data privacy important for a data consultant working with a global insurer or GCC client?

   Talk about personally identifiable information, regulatory expectations like GDPR or India's DPDP Act, and role-based access. Show that you would mask or aggregate data, avoid downloading sensitive files locally, and follow client data handling policies.

Technical skills and tools

1. 5

   Write a SQL query to find the top 5 cities by total premium collected, but only for policies active in the last 12 months.

   Cover SELECT, SUM, WHERE with a date filter, GROUP BY city, ORDER BY total DESC, and LIMIT 5. Explain that you would confirm the date column and active-status definition with the business before writing the query.

2. 6

   How would you use Excel to clean a list of 10,000 customer records with duplicate entries and inconsistent state names?

   Mention Remove Duplicates, TRIM and PROPER for text, Text to Columns, and a helper column with COUNTIF to flag duplicates. Add that you would keep a raw copy and document every cleaning step for reproducibility.

3. 7

   What is the difference between a left join and an inner join, and when would you use each in a claims dataset?

   Explain that inner join keeps only matching rows, while left join keeps all rows from the left table. Give an example: left join policies to claims to find policies with no claims, inner join when you only want policies that have claims.

4. 8

   How would you decide which chart type to use in a Power BI or Tableau dashboard for monthly claim trends versus regional comparison?

   Use a line chart for trends over time and a bar chart or map for regional comparison. Mention that you would keep the dashboard simple, label axes clearly, and avoid pie charts for more than three categories.

Practical scenarios and case thinking

1. 9

   A client says their claims processing time has increased by 20 percent in the last quarter. How would you investigate this as a data consultant?

   Structure the answer: clarify the metric and time period, break the process into stages, compare by region, product and channel, and check for data or system changes. End with a hypothesis and the data you would pull to test it.

2. 10

   You are asked to build a dashboard for a sales team, but you have no clear requirements. What do you do?

   Say you would interview two or three users, ask what decisions they make and how often, and draft a one-page mock-up before building. Mention agreeing on definitions, refresh frequency and success measures early.

3. 11

   Your analysis shows a drop in customer retention, but the business head disagrees and says the data is wrong. How do you handle it?

   Stay neutral, walk through your data sources, definitions and assumptions, and invite them to point out where they see a gap. Offer to validate with a second source or a small manual check, and document the agreed definition.

4. 12

   Estimate the number of health insurance claims a mid-sized Indian city processes in a month. Walk me through your approach.

   Break it into population, insurance penetration, average policies per household, claim frequency, and working days. State assumptions clearly, round sensibly, and sanity-check the final number against a known benchmark.

Behavioural and HR questions

1. 13

   Tell me about a time you worked with a team to meet a tight deadline. What was your specific contribution?

   Use a short STAR structure: situation, task, action, result. Focus on your individual action, such as taking ownership of data cleaning or coordinating a review, and end with a measurable outcome.

2. 14

   Describe a time you received critical feedback on your work. How did you respond?

   Pick a genuine example, not a humble-brag. Show that you listened, asked clarifying questions, changed your approach, and followed up. Avoid blaming others or saying you never get negative feedback.

3. 15

   Why do you want to work as a data consultant in a GCC or Big 4 environment rather than a product company?

   Talk about exposure to multiple clients or business functions, structured training, global stakeholders, and the consulting skill set of problem framing and communication. Connect it to your long-term interest in analytics and business strategy.

4. 16

   Where do you see yourself in three years, and how does this role fit that plan?

   Show a realistic path: strong delivery in year one, owning a workstream or client module by year two, and deepening domain or technical expertise by year three. Mention willingness to learn tools and domain areas as projects demand.