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Lead Strategic Partnership Data Analyst (Hybrid)
Posted Jul 1, 2026 · We last checked this listing on Sep 20, 2026
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Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
Behavioral
Walk me through a time you had to explain a complex analysis to a non-technical executive. How did you decide what to leave out?
whether the candidate can translate technical work into a clear business story for leadership audiences
Tell me about a project where you worked closely with account executives, data engineers, and finance at the same time. What made that hard?
ability to operate credibly across technical and business stakeholders with different priorities
Give me an example of a business metric you defined from scratch because none existed yet. How did you get stakeholders to agree on it?
comfort leading ambiguous, cross-functional metric definition work rather than just executing on given specs
Tell me about a time you found a data quality issue that was affecting a report leadership relied on. What did you do?
rigor in catching and resolving data integrity problems before they mislead decisions
Tell me about a time your analysis pointed to a conclusion that stakeholders didn't want to hear. How did you handle presenting it?
willingness to deliver fact-based recommendations under pushback, not just pleasant messaging
Tell me about a time you used an AI-enabled tool in your analytics work. What did it help with and where did you still need to apply your own judgment?
practical, honest experience with AI tools rather than buzzword familiarity
Technical
Write or describe a SQL query in BigQuery that would pull monthly performance trends for a set of national accounts, joining across at least two tables. What would you watch out for?
actual fluency with BigQuery/SQL and awareness of common join or aggregation pitfalls
How would you approach building a forecasting model for a book of business, and how would you decide when it's worth updating the model versus living with its current limitations?
practical judgment on statistical modeling and model maintenance tradeoffs, not just theory
Describe a manual reporting process you automated. What tools did you use and what broke along the way?
hands-on experience building and troubleshooting automated reporting pipelines
How have you used R or Python together with SQL in a single analysis workflow? Give a specific example.
whether the multi-tool experience claimed on a resume reflects real, integrated day-to-day use
What insurance product or pricing knowledge do you bring, and how has it changed the way you approached an analysis compared to someone without that background?
depth of actual insurance domain knowledge versus generic analytics skill
Situational
Say a dashboard you built in Tableau is technically correct but the account team says it doesn't answer their real question. What do you do next?
customer-driven mindset and willingness to iterate rather than defend the original output
If you noticed customer outcomes differing significantly by channel, say web versus contact center, how would you investigate whether that's a pricing issue, a product issue, or something else?
structured thinking about customer journey analysis across distribution channels, tied to the additional qualifications
You're given a dataset that's messy, undocumented, and needed for an executive presentation in two days. Walk me through how you'd triage it.
ability to produce reliable, analysis-ready output efficiently under ambiguity and time pressure
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As published by American Family Insurance.
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