Product Data Scientist at Clair
New York, NY
$200,000
Jun 28, 2026
New York, NY
Jul 21, 2026
What this job asks for AI summary
A senior individual-contributor role at a fintech company focused on earned-wage access, responsible for owning the full experimentation lifecycle — designing and analysing A/B and multivariate tests across both product surfaces and credit policies. The position also covers defining key metrics, building monitoring dashboards, and translating risk model outputs into business rules, sitting at the intersection of product, finance, risk, and engineering. Best suited to a quantitatively strong generalist with a background in product analytics and structured experimentation rather than large-scale ML engineering.
Senior level · 5+ years · New York-Newark-Jersey City, NY-NJ-PA · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 1,250 people in the New York-Newark-Jersey City, NY-NJ-PA area plausibly meet what this posting asks for (data scientists). range 920–1,600
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $135,980 (middle half $101,320–$173,160).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
The role sits at the intersection of product analytics and data science — the JD explicitly frames it as 'analytics + experimentation' rather than ML/modeling, which makes 15-2031 (Operations Research Analysts) a plausible alternative; 15-2051 was chosen because the title is 'Product Data Scientist' and the work involves statistical modeling, causal inference, and quantitative strategy.
No specific compensation figures are given — the posting describes only 'competitive base salary aligned with senior individual-contributor data roles in fintech'; no numeric range to extract.
Python and R are listed together as a single Nice-to-Have item ('Proficiency in Python or R'), so they are captured as one preferred skill with R as an alternative.
The title 'Product Data Scientist' carries no explicit seniority level word, so advertised seniority is Unspecified; the 5+ years requirement and cross-functional ownership scope support a Senior classification.
Experimentation platforms and statistical tooling are mentioned as a single Nice-to-Have item with no specific product named; captured generically as 'experimentation platforms' since no canonical tool is specified.
Fintech/lending/credit domain knowledge and underwriting concepts appear only under 'Nice-to-Have Experience' and are not captured as discrete tool skills — they are domain knowledge rather than named technologies.
Read the full posting
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