Willis Towers Watson India Data Consultant Interview: Rounds, Questions and Preparation

What the job involves

Data Consultants in GCCs, consulting firms and the Big 4 help clients make better decisions by cleaning, analysing and visualising data, often in domains like insurance, risk, health and rewards. A fresher typically works with senior consultants to build dashboards, run statistical models, validate data quality and translate findings into client-ready presentations. The role blends business understanding with hands-on tools such as Excel, SQL, Python or R and BI platforms.

Role and domain knowledge

1. 1

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

   Explain that a consultant combines analysis with client-facing problem solving, scoping, stakeholder management and recommendations, not just model building.

2. 2

   Why are GCCs and Big 4 firms hiring data consultants for insurance and risk clients?

   Mention growing data volumes, regulatory reporting, pricing and claims analytics, and the need to turn raw data into audit-ready insights for insurers.

3. 3

   Pick one common insurance metric, such as loss ratio or combined ratio, and explain how you would analyse it.

   Define the metric, show how you would break it down by product, region or time, and suggest what a rising or falling trend might indicate for the client.

4. 4

   How would you explain a complex regression output to a non-technical client stakeholder?

   Focus on business meaning, direction and size of effect, confidence in the result, and avoid jargon like p-values unless asked.

Technical skills and tools

1. 5

   Write a SQL query to find the top 5 customers by total premium paid in the last year from a transactions table.

   Show a GROUP BY on customer, SUM of premium, a WHERE filter on date, ORDER BY descending and LIMIT 5. Mention handling nulls or duplicates.

2. 6

   How would you clean a dataset with missing values, outliers and inconsistent date formats before analysis?

   Describe a step-by-step approach: profile the data, decide on imputation or removal, treat outliers with business logic, standardise formats and document every change.

3. 7

   What is the difference between an inner join, a left join and a full outer join, with a small example?

   Use two small tables and explain which rows are kept in each case, then give a practical example like matching claims to policies.

4. 8

   You have a dataset of 1 million rows in Excel. What tools or techniques would you use to analyse it?

   Say Excel is not ideal at that scale; suggest SQL, Python with pandas or a BI tool, and mention sampling or aggregation to make it manageable.

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?

   Structure the problem: define the metric, segment by region, claim type or team, check data quality, then form hypotheses and suggest next data pulls.

2. 10

   You are asked to build a dashboard for a risk manager who wants to monitor exposure daily. What would you include?

   Cover key metrics like total exposure, concentration by category, trend over time, alerts for thresholds and a clean layout with filters.

3. 11

   Your analysis shows a surprising result that contradicts the client's expectation. What do you do?

   Validate the data and method first, then present the finding with caveats and possible explanations, and suggest a follow-up check rather than forcing the expected answer.

4. 12

   You have two days to prepare a client presentation and the data is incomplete. How do you proceed?

   Prioritise the most decision-relevant analysis, document assumptions clearly, flag gaps to your manager and propose what can be done once data is complete.

Behavioural and HR questions

1. 13

   Tell me about a time you worked in a team to solve a data-heavy problem. What was your contribution?

   Use STAR format, highlight your specific analytical role, how you coordinated with others and the measurable outcome.

2. 14

   Why do you want to join a consulting or GCC environment rather than a product company?

   Show awareness of client variety, fast learning cycles, exposure to multiple domains and the consulting style of problem solving.

3. 15

   Describe a situation where you had to explain a technical finding to someone without a technical background.

   Focus on how you simplified the message, used visuals or analogies, checked understanding and adapted to the audience.

4. 16

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

   Align your growth with deepening domain expertise, leading small workstreams and adding more advanced analytics skills, while showing commitment to the firm.