S&P Global AI Research Scientist interview typically runs 3 rounds: online aptitude test, virtual technical interview, and in-person HR/technical round. The process is notably finance-heavy, emphasizing investment and accounting knowledge over coding.
$165K
Avg. Base Comp
$230K
Avg. Total Comp
3
Typical Rounds
2-4 weeks
Process Length
Our candidates report that S&P Global's AI Research Scientist process is far more finance-weighted than the job title implies. The standout pattern from what we've seen is how quickly the technical interview pivots away from modeling or ML methodology and into investment and accounting fundamentals — one candidate was walked through cash flow analysis, share buybacks, stock splits, and how bonus issues appear in financial statements. That's not a warmup question; that is the interview.
What makes this tricky is the deceptive simplicity of the questions. The wording is plain, but the expected depth is not. Interviewers here seem to probe whether you can reason about financial data the way an analyst would, not just whether you can describe an algorithm. The real signal they're looking for is whether your AI work is grounded in genuine financial domain knowledge — candidates who can only speak to the technical side without connecting it to how business events flow through the numbers appear to struggle here.
The final in-person stage adds a communication and culture-fit dimension, which suggests S&P Global is also evaluating whether you can translate complex ideas clearly to non-technical stakeholders. Taken together, the process rewards candidates who sit at the intersection of quantitative rigor and financial literacy — not just strong AI researchers who happen to be applying to a finance firm.
Synthesized from 1 candidate report by our editorial team.
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Featured question at S&P Global
Describing a data project and its challenges
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Synthesized from candidate reports. Individual experiences may vary.
The process begins with an online test covering aptitude, technical knowledge, and problem-solving ability. This stage is designed to screen for general reasoning and baseline domain understanding before advancing candidates to later rounds.
Candidates complete a one-on-one technical interview conducted over an online meeting. Despite the AI Research Scientist title, the discussion is heavily finance-focused, covering investment fundamentals, cash flow analysis, and how corporate actions such as share buybacks, stock splits, and bonus issues appear in financial statements.
The final stage is an in-person face-to-face round that blends HR and technical questions. This round assesses communication skills, cultural fit, and the candidate's ability to discuss both domain knowledge and behavioral topics in a live setting.
