Jobs / United States / Pinterest INC
Data Scientist II, Infrastructure
Pinterest INC · 🇺🇸 San Francisco, CA, US; Remote, US · 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 218 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 53 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 Pinterest INC paid sponsored hires in similar roles1 certified filing for “Data Scientist II” (Data Scientists) in MA: $162k–$162k, median $162k. 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.
Or apply yourself on the official page →
Sponsor Radar — Pinterest INC
The US Department of Labor certified 218 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 53 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 Pinterest INC →
About the role
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest brings millions of people the inspiration to create a life they love. Behind that experience is a complex infrastructure ecosystem that powers reliability, performance, measurement, and efficiency across the platform. As Pinterest grows, it’s increasingly important that we understand these systems clearly so we can make smarter decisions for both Pinners and the business. We’re looking for a Data Scientist to join our Infrastructure Data Science team. In this role, you’ll partner with engineering and cross-functional teams to make Pinterest’s infrastructure more measurable, intelligible, and actionable. Depending on the area, your work may span app performance, shopping infrastructure, metrics quality, infrastructure governance, or site reliability. You’ll help build the data foundations, measurement systems, and analytical frameworks that enable Pinterest to optimize core technical systems and make better product and infrastructure decisions. What you’ll do: In this role, you will partner closely with engineering and cross-functional teams to improve how Pinterest measures, understands, and optimizes its infrastructure: • Partner with engineering teams to define, measure, and improve the health, quality, and efficiency of Pinterest’s infrastructure systems. • Build and refine metrics, dashboards, and analytical frameworks that make complex technical systems more understandable and actionable. • Strengthen data foundations by improving metric definitions, auditing data quality, and contributing to pipeline and measurement improvements where needed. • Design and analyze experiments, investigations, and deep dives to quantify the impact of infrastructure changes on user experience, reliability, and business outcomes. • Translate ambiguous technical problems into clear analyses and actionable recommendations for engineering and platform partners. • Support high-priority investigations and decision-making related to infrastructure performance, reliability, cost, and measurement quality. • Identify opportunities to improve how Pinterest measures and optimizes infrastructure across a range of domains, such as performance, shopping infrastructure, governance, metrics quality, and site reliability. What we’re looking for: • Masters degree in a relevant field such as Statistics, Applied Math, Biostatistics, or equivalent experience. • Strong SQL and analytical programming skills, with experience working through messy, imperfect data and building reliable metrics and datasets. • Experience partnering on or contributing to production-ready data pipelines, measurement systems, or foundational data w