Higgsfield AI is the fastest-scaling generative AI company in history, hitting $500M in annual revenue run rate, 25M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We’re building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn’t just moving fast, but rewriting what fast looks like.
What This Role Means at Higgsfield
This role owns how Higgsfield measures its product - from the first sign-up to whether people come back.
You are the measurement owner for onboarding, first generation, the paywall, plans and credits, and retention. Product managers ship fast here - your job is to make sure they ship knowing.
You make sure:
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Every product decision has a number attached to it before it ships and after it ships
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Experiments are designed to be readable, and then read honestly - including when the answer is “this didn’t work”
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The events the product emits can be trusted; you own the definition, not just the query
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A PM gets an answer in hours, not next sprint
You are the person who decides what “it worked” means.
What You Will Do
Product measurement
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Own the core product metrics: activation, first-generation success, generation depth, free→paid conversion, repeat usage, retention by cohort and segment.
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Define each metric once, write the definition down, and hold the line on it - one definition across dashboards, decks, and Slack.
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Instrument new features before launch, with product and engineering: which events, which properties, what success looks like, when we call it.
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Watch the health of the event stream itself - tracking drift, double counting, missing parameters, naming breakage and find the problem before a decision gets made on top of it.
Experimentation
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Design A/B tests properly: hypothesis, one primary metric, unit of randomization, MDE, sample size, run length, guardrail metrics.
Separate “we proved this works,” “we proved this doesn’t,” and “we can’t tell from this test” - and say which one out loud.
Product & monetization analysis
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In-product funnel work: onboarding and quiz, first generation, paywall, checkout, plan choice, credit top-ups.
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Pricing and packaging analysis: plan mix, credit consumption, unit economics per generation, margin by feature and by model.
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Feature adoption and its real effect on retention and revenue — separating “users who do X retain better” from “making people do X improves retention.”
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Behavioural segmentation: casual creators vs corporate/B2B, new vs returning, by model and by use case. Mixing them hides everything that matters.
Making it usable
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Build the few dashboards PMs actually open on their own — decision-shaped, not comprehensive.
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Write short readouts a non-analyst can act on. Visualize data for humans, not for other analysts.
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Automate recurring reporting so your hours go to new questions, not refreshes.
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Work in SQL, Python, BigQuery and product analytics tools. We use AI heavily - resourcefulness beats syntax.
Who We’re Looking For
We’re looking for an analyst with opinions.
You should have:
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Strong SQL: window functions, cohorts, funnels and retention on raw event data, without help.
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Python at working level for analysis (pandas, notebooks). Entry level is fine - we use AI heavily.
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Real experimentation experience: you have designed tests, run them, and killed features with the results.
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Statistical honesty: you know what a p-value does and does not entitle you to say, and you have refused to call a flat test a win.
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Understanding of subscription + one-time purchase mechanics: recurring vs one-off revenue, refunds, plan changes, deferred value of unspent credits.
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The instinct to check the instrument before explaining the movement - a surprising number is a claim, not a fact.
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Ownership: you decide what’s worth analyzing, you chase the fix, you follow the recommendation to a shipped change.
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Clear written and spoken English, B2+.
Backgrounds that often do well:
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Product analysts from consumer subscription or PLG products
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Growth/BI analysts who moved into product and stayed
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Early-startup analysts who built product measurement from zero
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Data scientists who got tired of models and want decisions
What This Role Is Not
This role is not a fit if you:
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Wait for a ticket to tell you what to analyze
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Want to build models more than you want to change decisions
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Need a data engineering team and clean tables to exist before you can start
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Would report a lift you don’t believe in because a stakeholder wants it
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Need perfect data before you can say anything useful
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Want predictable 9–5 workdays
Hiring Process
We move fast:
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Screening call (30 min)
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Technical interview & case study (1 hour)
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Practical home task (7 days)
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Team interview (60 min)
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Paid on-site trial (1 month)
What We Offer
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Competitive base salary in USD, based on your experience, skills, and the scope of the role.
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Equity participation through the company’s stock option program, giving you the opportunity to share in Higgsfield’s long-term growth.
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Relocation support to Almaty for candidates moving from another city or country.
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A highly collaborative, fast-paced environment where you can work directly with experienced leaders and have a meaningful impact on the product and company.
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Opportunities for professional growth, ownership, and career development as the company scales.
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Company-provided equipment, meals, transportation, or other office benefits.