Jobs / United States / Replit INC
Data Scientist, Growth
Replit INC · 🇺🇸 Foster City, CA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 26 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 1 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Replit INC paid sponsored hires in similar roles2 certified filings for “Staff Data Engineer” (Data Scientists) in CA: $195k–$211k, median $203k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Replit INC
The US Department of Labor certified 26 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 1 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Replit INC →
About the role
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. ABOUT THE ROLE You'll be one of the founding data scientist on Replit's Growth team, working with Product and Engineering leadership across acquisition, activation and recommender systems, and helping shape how Replit experiments. This role is for someone who doesn't wait to be asked. You spot problems and opportunities before anyone else does, bring a strong point of view, and push it until it changes what we build. YOU WILL: - Own data science for major growth areas, partnering with PMs and engineers from problem framing and sizing through launch and readout - Make fast decisions trustworthy: we ship weekly and need a decision within days, but retention takes weeks to show up. You'll design the experiments and metrics that close that gap; for example, variance reduction (CUPED), sequential testing, and short-term proxy metrics validated against long-term retention and revenue - Help set the experimentation standards teams rely on for Replit's highest-traffic surfaces: how metrics and guardrails are defined, and the checks that catch a broken test before it misleads anyone - Use quasi-experimental designs (difference-in-differences, synthetic control, regression discontinuity) where randomization isn't feasible, such as pricing changes and regional launches - Help define the data science behind an emerging personalization and recommendations workstream: problem framing, offline and online evaluation, and measuring incremental lift - Model the economics of a freemium, usage-based product: credit consumption, conversion, and how pricing and limits change behavior - Develop user and project segmentation from behavioral and content signals (e.g., embeddings and clustering) so growth analysis reflects what people are actually building - Partner with Data Engineering on a shared metrics layer and experimentation tooling REQUIRED SKILLS AND EXPERIENCE - 6+ years in data science, with significant time on growth or experimentation for high-scale prosumer, PLG, or self-serve products - Data science experience at a fast-growing startup, where you built metrics, datasets, and experimentation practices without much existing infrastructure - Deep expertise in experimental design and statistical inference, including reaching reliable decisions when readout windows are short and the outcomes that matter are slow - Experience establishing experimentation standards or platforms adopted by multiple teams - Expert SQL and Python - A track record of analysis that changed what a team shipped, and of influencing senior Product and Engineering leaders - Heavy, practical use of AI tools to move faster in your own work PREFERRED QUALIFICATIONS - Comfortable building your own datasets in dbt; - Pricing, packaging, or monetization analysis for usage- or credit-based products - International or mobile growth experience - MS or PhD in statistics, economics, computer science, or another quantitative field BONUS POINTS - Experience with multi-armed bandits or adaptive experimentation - Familiarity with developer tools, AI products, or creator platforms This is a full-time role based in our Foster City, CA office with an in-office requirement of Monday, Wednesday, and Friday. Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays �