EY data scientist interviews, as candidates describe them, combine recruiter or HR screens, technical rounds on SQL, Python and ML, resume project deep dives, and a manager, partner or client conversation.
$158K
Avg. Base Comp
$185K
Avg. Total Comp
2-5 rounds
Typical Rounds
4-56 days
Process Length
Candidates describe EY data scientist interviews as a mix of technical questioning and conversations about fit, and the resume project deep dive comes up in most accounts. One candidate faced a three-person panel covering data science, SQL, Power BI and HR, with follow-ups on why one approach was chosen over another. Another reports that a partner asked them to explain every project before moving to HR questions. Expect to defend design choices, not just describe results.
Technical content varies by account. Candidates mention SQL and Python (including DataFrame, list and array coding problems), core algorithms such as linear and logistic regression, and R-squared. LLM, NLP and RAG topics appear in several reports, and one candidate with a computer vision background was asked about FRCNN, YOLO and data augmentation. Time series appears in two accounts, covering cross-validation of a forecasting model and autocorrelation with ACF and PACF plots.
Later rounds lean toward people and client skills. Reported formats include a manager conversation about teamwork, a client-facing conversation, and a case study panel where the candidate presented as if to clients. Structure your answers for a business audience as well as a technical one.
Reported process shapes range from two rounds within four days to four or five rounds over roughly five to eight weeks, so ask your recruiter what to expect. Outcomes in these reports include offers and declined offers, and one candidate was rejected.
Synthesized from 7 candidate reports by our editorial team.
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Real interview reports from people who went through the Ey process.
I got a direct invitation from HR through LinkedIn to attend a hiring drive at EY's Kochi office in February 2025. There were openings across different domains, which was good to know. The drive kicked off in the morning, and I went through two rounds.
The first round was conversational. The interviewer wanted me to walk through the technical details of my research work and explain why I was interested in EY and tech roles specifically. It felt pretty personable—the interviewer was polite and put me at ease. The whole thing took maybe thirty minutes.
The second round was where things got more technical. They dove into data science and machine learning concepts, asking me to think through problems verbally. One question stuck with me: how would I cross-validate a time series forecast model? They also asked me to reason through different forecasting methodologies and clustering techniques, and I got to share some sketches to illustrate my thinking. At the end, they had me present my approach and findings from the technical part, which felt like a good way to wrap up—letting me show both my analytical thinking and communication skills.
Prep tip from this candidate
Go deep on time series cross-validation and forecasting methodologies—be ready to discuss multiple approaches for different scenarios. They'll want you to reason through assumptions out loud, so practice verbalizing your data science thinking, not just writing code.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
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Synthesized from candidate reports. Individual experiences may vary.
Candidates typically report an opening conversation with a recruiter or HR contact about their background, projects and role expectations. One candidate also describes a casual coffee chat with an employee after the screen. Treat it as a chance to rehearse a concise project summary and confirm logistics.
Candidates report technical rounds covering SQL, Python libraries and coding problems, statistics, and core ML algorithms. Some accounts add LLM, NLP, RAG, MLOps or time series topics. Depth reportedly varies by interviewer and background, and one junior-level candidate found the bar higher than expected.
Several candidates say interviewers walked through resume projects in detail and pushed with follow-ups about alternative approaches, challenges and how results were communicated to business stakeholders. Prepare two or three projects you can explain end to end, including trade-offs and what you would change.
Some candidates describe a case study panel or a verbal problem-solving round where they structured an approach and presented findings, in one case as if to clients. This format is not reported by everyone, but it may reward clear framing and out-loud reasoning.
Final conversations are reported with a senior manager, a partner or a client, covering team experience, management style, project walkthroughs and behavioral questions. Candidates generally describe these as more conversational than the technical rounds, though one was surprised that the partner asked them to explain every project before HR questions.
