Candidates describe an ISS Data Analyst process of three to four stages: an assessment or take-home, an HR conversation, and technical or manager conversations. Motivation is a common focus, and some reports add ESG interest and basic finance questions.
$73K
Avg. Base Comp
$85K
Avg. Total Comp
3-4 rounds
Typical Rounds
Not reported
Process Length
Candidates who interviewed for ISS data analyst roles, including junior titles, describe a process that leans toward motivation and fit more than hard technical drilling. Reports vary in structure: some mention three rounds, one describes four, and another starts with a take-home followed by a code walkthrough and an HR Q&A.
Be ready to explain why you want to work in ESG and at ISS. One candidate who received an offer said this question came up at every stage. Others report being asked what they knew about the company, why they wanted the role, and how their background fit. Reviewing the company's ESG focus beforehand looks worthwhile.
The technical side appears to be moderate. Reported formats include an aptitude test, a written test, a self-paced assessment with a deadline, and a take-home coding task. One candidate was asked to explain their code and discuss practical Python skills such as merging dataframes. That candidate was also asked about the Fama-French three-factor model. Another report mentions only light financial and ESG-standards questions, so basic finance literacy is probably enough to prepare for, rather than deep capital-markets theory.
Behavioral questions reported include strengths and weaknesses, handling stress, and a conflict with a colleague. Prepare concrete project examples that connect your past work to the role. Candidates describe interviewers as friendly and conversational. Three of the five reports ended without an offer, so clear, specific alignment between your background and the role matters. The evidence is limited, so treat the stage order as one of several reported variations.
Synthesized from 5 candidate reports by our editorial team.
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Real interview reports from people who went through the Institutional shareholder services process.
I started with a take-home coding assessment, which was the initial filtering round. Once I passed that, I was invited back to explain my code and answer some technical questions — they wanted to understand my approach and reasoning, not just the final solution. The technical round covered a mix of analytics concepts and practical skills like merging dataframes in Python. What surprised me was the finance component. They asked about the Fama-French three-factor model, which caught me slightly off guard since I hadn't specifically prepped for financial theory, but it made sense given the investment services focus of the company. After that round, I had a Q&A session with HR where they covered standard behavioral territory — my strengths, work style, and fit with the team. The whole process took a few weeks from initial application to final offer, which felt reasonable. The team was genuinely engaged throughout and seemed to value understanding how I think about problems rather than just checking boxes. They also sent thoughtful feedback after each stage, which I appreciated even though the journey was longer than I'd anticipated.
Prep tip from this candidate
If you're interviewing here, brush up on finance fundamentals like the Fama-French model and other asset pricing concepts — that's domain-specific knowledge they clearly care about. Also, prepare to walk through your take-home code in detail and explain your design choices, not just get it working.
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Topics based on recent interview experiences.
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Synthesized from candidate reports. Individual experiences may vary.
Candidates report an early filter, described variously as an aptitude test, a self-paced assessment with a deadline, a written test, or a take-home coding task. Reports call it fairly straightforward. Basic preparation in practical data skills should help, and the format may differ by role or level.
Candidates report an HR conversation covering tell-me-about-yourself, why ISS and the role, what you know about the company, and ESG interest. Behavioral questions on strengths, weaknesses, stress and workplace conflict were also mentioned. Interviewers are described as approachable and conversational.
One candidate was asked to explain their take-home code and answer technical questions, including merging dataframes in Python and the Fama-French three-factor model. Another reports a roughly 30-minute technical interview testing practical knowledge. Not every candidate describes a technical round, so expect this to vary.
Some candidates report a later round with a hiring manager, or a panel of team members and stakeholders. One described it as confirming qualifications and cultural fit more than testing technical depth. One candidate was also asked to link past projects to the role, so prepare specific examples.
