KPMG Data Analyst interviews typically run 3–5 rounds: online assessment, HR screening, technical interview, and a managerial or partner round. The process takes 2–3 weeks and is notably communication-heavy, emphasizing fit and motivation over deep technical grilling.
$72K
Avg. Base Comp
$130K
Avg. Total Comp
3-5
Typical Rounds
2-4 weeks
Process Length
What we've seen consistently across KPMG Data Analyst candidates is that the process is front-loaded with communication and motivation screening — and that's where most people actually get filtered out. Multiple candidates reported that rounds like group discussions, HR calls, and even assessment centre exercises were less about demonstrating technical mastery and more about whether you could articulate why KPMG, why this role, why now in a clear and confident way. Candidates who stumbled here rarely made it to the more substantive rounds, regardless of their technical background.
The technical bar, when it does appear, is narrower than you might expect for a Data Analyst title. A recurring theme is that KPMG leans heavily on accounting and audit fundamentals — balance sheet walkthroughs, IFRS concepts, P2P process explanations — rather than the kind of SQL-heavy or Python-intensive grilling you'd see at a tech company. That said, a few candidates on the analytics track specifically flagged SQL, basic Python, and tools like Power BI and Alteryx as areas that came up, so the exact technical angle shifts depending on the team. One candidate was asked a murder mystery-style database reasoning question; another was asked to infer a company's industry from its balance sheet. The pattern is applied thinking, not rote recall.
The non-obvious thing that makes or breaks interviews here is scenario-based fluency. KPMG interviewers consistently created situations on the spot — how would you audit this process, what does this balance sheet tell you, how did you handle a conflict — and they were evaluating how you reasoned out loud rather than whether you landed on a perfect answer. Candidates who accepted offers tended to describe the process as conversational and fair; those who didn't often noted they were caught off guard by how much the firm cared about motivation and fit relative to hard skills. Coming in with a polished personal narrative and comfort with core financial concepts matters more here than it might at a pure analytics shop.
Synthetized from 15 candidates reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the Kpmg process.
What stood out to me most was how much of the process was designed to filter for communication and fit before they really dug into technical ability. I had four rounds overall: an aptitude round, a group discussion, an assessment, and then a face-to-face HR interview. The group discussion was very much about participation and confidence, not just having the right answer. The topic I got was the effect of social media on the real world, and it was clear that they wanted to see whether I would actively contribute instead of just sitting back. That was the first big gate.
After that came the assessment and then the HR conversation, which felt more like a structured fit check than a deep technical interview. They asked me to describe myself and explain how I fit the job, along with questions about my studies, work experience, and why I was interested in the role. In the technical part, the most important question was scenario-based and centered on valuations, so they were testing whether I could think through a business case rather than just define terms. The whole process moved fairly quickly, and they were responsive after the application, but it was still pretty selective. My impression was that KPMG cared a lot about how you present yourself, how you handle discussion, and whether you can connect your background to the role. I didn’t get an offer in the end, so I’d say the safest prep is to practice speaking clearly in a group setting, be ready to explain your background and motivation, and review valuation scenarios so you can talk through them confidently.
Prep tip from this candidate
Practice speaking up early in a group discussion, because active participation was treated as a screening criterion. Also prepare a clear explanation of your background and a scenario-based valuation answer, since that was the main technical prompt.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Kpmg
Describing a data project and its challenges
| Question | |
|---|---|
| Assumptions of Linear Regression | |
| Spam Classifier | |
| Data Preparation for Imbalanced Data | |
| Multicollinearity in Regression | |
| Algorithm Reliability | |
| Why Do You Want to Work With Us | |
| Your Strengths and Weaknesses | |
| 2nd Highest Salary | |
| Experiment Validity | |
| Raining in Seattle | |
| Bagging vs Boosting | |
| Revenue Retention | |
| Using R Squared | |
| Sort Strings | |
| Find Duplicate Numbers in a List | |
| Classification and Regression | |
| Missing Housing Data | |
| Bias vs. Variance Tradeoff | |
| Overfit Avoidance | |
| FAQ Matching | |
| Slow SQL Query | |
| Swap Variables | |
| String Palindromes | |
| Stakeholder Communication | |
| Simple Explanations | |
| Youtube Recommendations | |
| Xgboost vs Random Forest | |
| Data Cleaning Experiences | |
| User Journey Analysis |
Synthesized from candidate reports. Individual experiences may vary.
Candidates submit a resume and cover letter, then complete online assessments that may include cognitive/aptitude tests, logical reasoning, abstract reasoning, a personality section, and sometimes a written task such as drafting a professional email. Some tracks also include recorded video responses at this stage.
An initial phone or video call with HR focused on background, motivation, and fit. Expect questions like 'Tell me about yourself,' 'Why KPMG,' and 'Why this role,' along with a review of your CV and career goals.
Some candidates attend an assessment centre that includes a group exercise or case study discussion, a Q&A session with an employee, and occasionally a game component. Active participation and clear communication are evaluated more than having the single correct answer.
A structured interview with a senior associate, manager, or technical lead covering role-specific skills. For Data Analyst roles this includes SQL, basic Python, data analytics concepts, and scenario-based questions; for audit-adjacent roles it focuses on accounting fundamentals such as balance sheets, IFRS, and process walkthroughs like P2P.
A conversational one-on-one with a partner, director, or senior manager that emphasizes long-term motivation, career goals, and cultural fit. Questions tend to be behavioral and situational rather than deeply technical, and may include topics like time management and professional judgment.
A closing conversation with HR covering cultural fit, salary expectations, and any remaining questions about the role or firm. This stage serves as a final check on motivation and communication before an offer decision is made.