Dun & Bradstreet Data Analytics Interview Questions and Answers (2026 Guide)

Quick answer: Dun & Bradstreet's core product is commercial credit data and business risk scoring, and its India operations, headquartered in Mumbai, run a Trade and Credit Risk Analytics data-science function serving global clients. One detailed candidate account for a Chennai-based technical role describes a 3-level process, and SQL practice questions tied to D&B's own credit-scoring domain exist, though most of what we found reflects one candidate's experience rather than a large, verified sample.

About Dun & Bradstreet

D&B is a global business-decisioning data provider whose core products are commercial credit data, risk scoring and business analytics, including its D-U-N-S numbering system. D&B India, headquartered in Mumbai, runs analytics operations feeding the global business, including a Trade and Credit Risk Analytics data-science function that builds B2B risk models for global clients, including Fortune 500 companies. (D&B careers listing, Analyst II Data Science)

D&B's Interview Process

• General D&B India pattern reported on Glassdoor: a recruiter phone screen of about 30 minutes, followed by two further rounds, one HR round conducted in person and one technical round conducted online. (Glassdoor)

• A detailed Chennai-based candidate account (around July 2022) describes a 3-level process: Level 1 covered Python and pandas questions such as groupby and min/max operations, machine-learning theory like linear regression and decision trees, and SQL; Level 2 was a live data-handling task, loading a dataset in Python, computing central-tendency measures per column, finding maximum values and the full rows they belong to, and plotting line charts with correlation analysis between continuous variables; Level 3 was an HR round covering background, five-year career goals, career gaps, and ability to work under pressure. (Glassdoor)

What Candidates Report

The one genuinely D&B-flavoured detail we found is SQL practice questions tied specifically to its business domain: computing average monthly or industry credit scores using window functions and common table expressions, and filtering businesses by credit-score range and payment status, rather than textbook SQL. (DataLemur) Current job postings for D&B's Mumbai Analyst, Data Science role explicitly describe modelling work using XGBoost, LightGBM, Random Forest and logistic regression for B2B risk solutions, which is a real, current basis for what a technical round is likely to probe, even though it is a role requirement rather than a confirmed interview question.

What We Could Not Verify

Only one detailed India-specific candidate account was found, for a Chennai role, so we are not presenting its exact structure as universal across all D&B India hiring. Glassdoor pages could not be directly fetched (only search-indexed summaries were accessible), and AmbitionBox returned nothing usable.

How to Prepare

• Practise pandas fundamentals specifically: groupby operations, central-tendency measures, and correlation analysis between variables, all directly reported.

• Revise SQL window functions and CTEs in a credit-scoring context, since D&B's own practice questions are framed this way.

• Know XGBoost, LightGBM, Random Forest and logistic regression at a working level, given current role postings name them directly.