Jobs / United States / Reddit INC
Senior Director, Data Science
Reddit INC · 🇺🇸 Remote - United States · Remote
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 66 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 40 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 Reddit INC paid sponsored hires in similar roles3 certified filings for “Machine Learning Engineer” (Data Scientists) in WA: $245k–$264k, median $260k. Most were filed at wage level III (67%) — 3 lottery entries, ≈46% 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 — Reddit INC
The US Department of Labor certified 66 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 40 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 Reddit INC →
About the role
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is seeking a Senior Director of Consumer Data Science to lead a multi-team organization that partners across Consumer, Product, Engineering, and the broader business. You will set the strategy and operating model for consumer data science, strengthen the systems and standards that make scientific outputs reliable, actionable, and scalable, and guide high-impact decisions through measurement, experimentation, causal inference, and ML. This leader will help define how Reddit measures and improves relevance across the consumer journey—from retrieval and ranking to feed, search, recommendations, and community discovery—and will shape the organizational capabilities required to advance these systems over the long term. Accordingly, the role requires the technical depth to evaluate architecture and analytical investments, guide state-of-the-art ML system improvements, and the leadership presence to align senior leaders around difficult tradeoffs. What you’ll do • Partner with senior leaders across Consumer, Product, Engineering, and business functions to define company-level bets, priorities, and tradeoffs. • Set the data science strategy for Reddit’s feed, recommendation, search, retrieval, and ranking systems, including objective design, candidate generation, ranking quality, relevance evaluation, experimentation, and long-term optimization. • Establish the measurement and experimentation framework for relevance optimization, including offline evaluation, online experimentation, counterfactual analysis, guardrail metrics, metric integrity, and the connection between model improvements and consumer and community outcomes. • Translate complex user and community behavior into clear, impartial insights that improve product strategy and consumer outcomes. • Establish durable standards for measurement, experimentation, causal inference, reproducibility, privacy, responsible AI use, and self-serve measurement, at scale. • Build multi-team roadmaps, operating cadences, and clear accountability that turn company direction into durable delivery. • Exercise strong technical judgment across architecture choices, analytical systems, hiring, and sponsorship of high-leverage programs. • Build or rebuild systems and practices that make analytical work reliable, adoptable, and scalable rather than dependent on individual heroics. • Recruit, retain, and develop exceptional Directors, managers, and IC5+ leaders across multiple teams or pillars. • Set a high talent bar through succession planning, calibration, and clear expectations for coaching, performance, accountability, and growth. • Create durable cross-org forums and operating mechanisms that improve coordination, culture, and decision quality. • Align senior product, engineering, and business leaders on measurement strategy, difficult tradeoffs, and decisions with material multi-year impact. • Represent Reddit externally and internally as an acknowledged thought leader and visible culture shaper for rigor. • Partner with teams advancing ML and analytical systems that deepen understanding of Reddit’s UGC and community ecosystem. Skills and Qualifications • Deep data science expertise in measurement, experimentation, causal inference, ML, data platforms, and analytical systems, with the technical judgment to set company-scale