Product Analytics and Experimentation Expert

$115/hr

rate as listed

Workload: 10+ hrs/week
Location: Location not stated
Field: Sciences

Author realistic product analytics problems and reference answers covering experimentation, metrics, retention and growth. The work is remote and asynchronous, with a minimum commitment of 10 hours per week.

The work

You will turn product decisions into realistic analytics problems for frontier AI evaluation. Day to day, this means framing questions about experiments, metrics, retention and growth, working each problem through to a reference answer, documenting the reasoning behind every step, and identifying plausible analytical mistakes that an experienced practitioner would catch.

What afterquery screens for

The platform looks for at least 3 years of full-time experience as a data scientist or product analyst on a product team, excluding internships and school. Candidates need hands-on A/B test design or analysis experience. Required technical qualifications are strong SQL, Python and applied statistics, along with strong written English and the ability to explain an analysis clearly. A Master's degree in a quantitative field is preferred, as is experience defining product metrics or modeling retention and lifetime value.

Practical details

This is a remote, project-based independent contractor role. Work is fully async, with no fixed hours, a minimum commitment of 10 hours per week and no maximum. Contributors may scale their time up or down from week to week. Payment is weekly through Stripe, and the platform states that it does not use screen recording, keystroke monitoring or idle timers.

Pay band: $115/hr

What they look for

3+ years of full-time product-team experience as a data scientist or product analyst
Hands-on A/B test design or analysis
Strong SQL and Python
Applied statistics for product decisions
Clear written English and analytical explanation
Product metric definition, retention modeling or lifetime value modeling

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This tests whether the candidate has at least 3 years of qualifying product-team experience and can connect analysis to actual product decisions rather than academic exercises or reporting alone.
A strong answer: Give dates, employers or product contexts, responsibilities and one or two decisions influenced by the work. Separate full-time experience clearly from internships, education or unrelated analytics roles.
Where people lose it: Counting internships, school projects or general business intelligence work toward the 3-year requirement without showing direct participation in product decisions.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.