Jobs / United States / Discord INC
Staff Data Scientist, Causal Inference & Experimentation
Discord INC · 🇺🇸 San Francisco Bay Area
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 23 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 6 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 Discord INC paid sponsored hires in similar roles5 certified filings for “Senior Data Scientist” (Data Scientists) in CA: $220k–$272k, median $265k. Most were filed at wage level IV (60%) — 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 — Discord INC
The US Department of Labor certified 23 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 6 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 Discord INC →
About the role
Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. Discord's Experimentation Platform puts data at the heart of the company's decision-making and growth - we run hundreds of experiments at any given time, and those results turn directly into business decisions across Discord. As a Staff Data Scientist on this team, you will ensure that the statistical underpinnings of our experiments are sound, that experimenters are able to design experiments with high rigor, and that Discord makes the best business decisions on the basis of these experiments. We are a small and quickly growing team; you will be presented with significant leadership opportunities as we evolve. Our team directly impacts the strategy and roadmaps that improve Discord for its more than 90M daily active users! If helping make Discord an even better place to hang out with your friends sounds like an exciting challenge - we'd love to chat with you! What you will be doing • Formulate the vision and set the roadmap for the future of the Experimentation Platform, in partnership with engineering, product, and data science stakeholders. • Provide statistical expertise, ensuring that experimentation methodologies and frameworks are sound and aligned with best practices in causal inference and experimental design. • Partner closely with engineering and product to improve the reliability, scalability, and adoption of experimentation across Discord - including modern AI/LLM tooling where it can accelerate rigor and speed. • Lead initiatives to educate and train cross-functional teams - including workshops, training sessions, and educational materials - on experimentation design, statistical methodology, and causal inference. • Empower Discord's Data Science team (50+ members) to adopt more rigorous causal inference methods. • Lead and conduct original causal inference research on high-priority Discord questions, in partnership with the wider Data Science team. • Engage directly with experimentation customers - data scientists, product managers, and engineers - to ensure the platform enables fast, reliable, data-driven decisions. What you should have • Proven experience leading experimentation platform work, including designing and validating statistical methodologies to ensure the accuracy and reliability of experimental results. • PhD in a quantitative field (e.g. Statistics, Economics, Political Science, Psychology) or equivalent practical experience, plus 4+ years designing, implementing, and analyzing experiments or causal inference projects. • Ability to critically evaluate and recommend statistical approaches that balance velocity and reliability across a variety of product launches. • Strong passion for education, with a track record of communicating complex statistical and experimental design concepts to technical and non-technical audiences and fostering a culture of data literacy. • Demonstrated experience in developing and delivering training programs or educational content related to experimentation, causal inference, or statistical analysis, with a track record of fostering a culture of data literacy within an organization. • Proficient with Python, SQL, R, and/or other statistical programming languages. Bonus Points • Interest in conducting literature reviews, translating and championing best scientific practices across the company. • Track record using causal inference methods that translated into business decisions and outcomes.