product analyst in generative AI

Higgsfield AI is a generative AI company developing AI-powered video creation and next-generation creative tools. Its products serve more than 25 million users worldwide and power 390 Fortune 500 brands.

• Own core product metrics including activation, first-generation success, generation depth, free-to-paid conversion, repeat usage, and retention by cohort and segment;
• Define product metrics consistently across dashboards, presentations, and Slack;
• Instrument new features before launch with product and engineering teams;
• Monitor event-stream quality, including tracking drift, double counting, missing parameters, and naming issues;
• Design A/B tests with hypotheses, primary metrics, randomization units, MDE, sample sizes, run lengths, and guardrail metrics;
• Analyze experiments for significance, peeking, novelty effects, sample-ratio mismatch, and segment heterogeneity;
• Distinguish proven success, proven failure, and inconclusive experiment results;
• Analyze product funnels across onboarding, quizzes, first generation, paywalls, checkout, plan selection, and credit top-ups;
• Analyze pricing, packaging, plan mix, credit consumption, unit economics, and margins by feature and model;
• Evaluate feature adoption and its effects on retention and revenue;
• Build behavioral segments across creator types, user status, models, and use cases;
• Build decision-focused dashboards for product managers;
• Write concise analytical readouts for non-analysts;
• Visualize data for practical decision-making;
• Automate recurring reporting;
• Work with SQL, Python, BigQuery, and product analytics tools.

• Strong SQL skills, including window functions, cohorts, funnels, and retention analysis on raw event data;
• Working-level Python skills with pandas and notebooks;
• Real experimentation experience, including designing and running tests and stopping features based on results;
• Strong statistical judgment, including understanding the appropriate interpretation of p-values and flat tests;
• Understanding of subscription and one-time purchase mechanics, including recurring and one-off revenue, refunds, plan changes, and deferred value of unspent credits;
• Ability to validate instrumentation before explaining metric changes;
• Ownership from deciding what to analyze through following recommendations to shipped changes;
• Clear written and spoken English, B2+;
• Not a fit for candidates who wait for tickets, prioritize model building over decision impact, require clean tables or a data engineering team, report untrusted lifts, need perfect data, or want predictable 9–5 workdays;
• Nice to have: experience as a product analyst in consumer subscription or PLG products, growth or BI analysis experience transitioned into product, experience building product measurement from zero in an early startup, data science experience focused on business decisions.

• Equity participation through the company’s stock option program;
• Relocation support to Almaty for candidates moving from another city or country;
• Professional growth, ownership, and career development opportunities;
• Company-provided equipment, meals, transportation, or other office benefits;
• Office work five days per week for the full working day.