Does anyone have the wisdom to share on what to look for when interviewing a Data Science partner for a growth team? Suggested role-specific interview questions would also be super helpful!
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I believe you could borrow several questions/case ideas from the data-driven technical PM questions I saw elsewhere in this Slack group, where you delve into processes and how to optimize processes and bump up the technical/implementation explain requirements.
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Context:
- Hyper-growth marketplace B2B marketplace startup.
- New growth squad (PM + 4Eng).
- The role would sustain growth marketing, product, and promotions approach to start.
- Given B2B, ideally, have encounter experimenting in “low n” contexts.
- Job description in case expedient.
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Having been on both sides of the table as an Analytics Professional and a Data Product Manager - I have few ideas.
Simpson’s Paradox is great.
a)You can also ask how would they run A/B Tests in a marketplace. Running A/B Tests in the marketplace is pretty interesting because of the dynamic name of supply, demand, and supply-demand interaction.
b)Also ask them, let us say X metric has gone up and Y metric has gone down. What would you prioritize?
c)Very important question - How does Data Science work with PMs and Engineers. Answers will surprise you
d) Ask them questions related to “Bias to Action” scenarios because you will need quick answers
e) Ask them - How long should the test be run?
f) Since it is a growth role - Ask them what would the funnel or flywheel at the fair would look like and which set of metrics would they prioritize. They should come up with a framework like Reach->Activation->Engagement->Stickiness->Retention->Revenue->Referral etc.
g) Ask them what do you think are the NSMs of Faire
h) Ask them the root cause analysis questions such as “Faire’s New App users have dropped 50% WOW. What could be the reason for it”
My intent is to test three things a) Raw intelligence b) Business Context c) Communication Skills.
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A bit behind to the party, but I’d add that the job description seems to be for databases or Product Analysts and not information Scientists. statistics Science is focused more on a bit delayed to the party, but I’d add that the job description seems to be for a statistics or Product Analyst and not a statistics Scientist. information Science is focused more on machine acquiring and statistics, rather information analyst is more embed into the product supporting A/B tests, defining and canny KPIs, metrics, running ad hocs, etc.
n machine acquiring and statistics, rather statistics analyst is more embed into the product supporting A/B tests, defining and canny KPIs, metrics, running ad hocs, etc.
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I’m always a fan of asking real-world example questions. Give them a real example of the kind of thing they’d be asked on the job and ask them to walk you through how to solve it
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