Jobs / United States / Plaid INC
Senior Data Scientist - Embedded Insights
Plaid INC · 🇺🇸 San Francisco HQ; Seattle Office; New York City Office
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 27 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 9 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 Plaid INC paid sponsored hires in similar roles1 certified filing for “Data Scientist” (Data Scientists) in IL: $180k–$180k, median $180k. 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 — Plaid INC
The US Department of Labor certified 27 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 9 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 Plaid INC →
About the role
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. ABOUT THE TEAM At Embedded Insights, we find the best machine learning opportunities for external products and internal systems, and collaborate with cross-functional partners to bring them to life. We are a central team of Machine Learning Engineers and Data Scientists. We embed with partner teams to build and apply machine learning models that improve internal decision-making and power the Plaid product suite. ABOUT THE ROLE You will be the first Data Scientist on the Embedded Insights team, part of Plaid’s Data organization. You will establish the analytics and metrics backbone for a team supporting a diverse set of internal and external products. You will help drive better decision-making, support machine learning model development, and contribute directly to the health of the Plaid network and the quality of Plaid’s products. Your day-to-day work will include: - Analyzing entities across the Plaid network to understand behavior and identify opportunities, anomalies, and risks. - Creating foundational metrics, dashboards, and monitoring systems that provide a clear view of network health and machine learning model performance. - Evaluating the value and performance of machine learning models using customer and internal data. - Identifying opportunities to improve existing models and translating findings into clear, actionable narratives for product and engineering leaders. - Designing experiments, defining success metrics and guardrails, analyzing results, and communicating recommendations to stakeholders. - Analyzing Plaid product and customer data to identify opportunities for product improvement and expansion. - Partnering with cross-functional teams to build reliable data models and analytics workflows. WHAT EXCITES YOU - Applying quantitative analysis, data mining, and data visualization to help keep the Plaid network healthy and improve our product suite. - Informing and influencing product and engineering teams through rigorous analysis, thoughtful presentations, and clear recommendations. - Turning ambiguous business questions into structured analytical approaches and measurable outcomes. - Helping shape long-term data science and machine learning roadmaps, including how teams iterate, evaluate, and make decisions. - Establishing analytics practices and frameworks from the ground up as the team’s first Data Scientist. - Championing a data-first approach to decision-making across Plaid. WHAT EXCITES US - 6+ years of industry experience in Data Science or a related analytics role. - Deep familiarity with SQL and data visualization tools. - Understanding of modern machine learning techniques, such as classification, clustering, and optimization. - Experience evaluating model performance, identifying opportunities for improvement, and connecting technical results to business outcomes. - Proven ability to tailor analytical solutions to business problems while working with cross-functiona