EY Data Scientist candidates reported project-defense discussions, SQL and data-modeling questions, business-case presentation, and behavioral conversations. Reported processes ranged from three to five rounds.
$133K
Avg. Base Comp
$149K
Avg. Total Comp
3-5 rounds
Typical Rounds
5-8 weeks
Process Length
EY Data Scientist interviews in the available reports center on explaining work clearly as well as discussing technical choices. One Data Scientist candidate described an intensive opening panel with data science, SQL, Power BI, and HR representation. The discussion repeatedly returned to resume projects, including LLM, NLP, Python, RAG, RCNN, SQL, and Power BI data modeling, with follow-ups about the consequences of different approaches. Prepare to defend what you built, why you chose the approach, and how you would respond when assumptions change.
A separate Data Science Consultant candidate reported SQL questions and a project deep dive, followed by a case-based panel that required structuring a solution and presenting it in a client-style format. Clear communication of technical work to business stakeholders was part of that candidate’s account. Later conversations may emphasize experience, teamwork, management style, and fit; one Data Scientist candidate also said senior-manager and partner conversations still included detailed project discussion.
The evidence is limited to two adjacent-role reports, so formats may vary by team. Practice a concise project narrative, then rehearse technical follow-ups and a structured business-case presentation rather than treating them as isolated skills.
Synthesized from 2 candidate reports by our editorial team.
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Synthesized from candidate reports. Individual experiences may vary.
One candidate reported a first round with three panelists covering data science, SQL, Power BI, and HR. Their resume projects drove follow-up questions on LLMs, NLP, Python, RAG, RCNN, SQL, and Power BI data modeling, with emphasis on defending design choices.
A Data Science Consultant candidate reported SQL questions and a project explanation covering technical work, challenges, responses, and communication to business stakeholders. The same candidate then described a panel case study requiring an approach, solution, and client-style presentation.
One Data Scientist candidate described a senior-manager conversation about personal experience, teamwork, team-management style, and team projects, followed by a partner call that began with detailed project explanations before HR questions. Another candidate reported a final behavioral round.
