Jobs / United States / Social Finance INC
Staff Data Scientist
Social Finance INC · 🇺🇸 Add ALL locations here
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 186 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 49 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 Social Finance INC paid sponsored hires in similar roles3 certified filings for “Staff Data Scientist” (Data Scientists) in NY: $200k–$250k, median $216k. Most were filed at wage level IV (67%) — 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 — Social Finance INC
The US Department of Labor certified 186 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 49 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 Social Finance INC →
About the role
Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. SoFi Bank N.A. seeks Staff Data Scientist in San Francisco, CA: Job Duties: Identify opportunities and collaborate cross functionally to develop, implement, and continuously improve machine learning models and strategies that support credit underwriting. Identify opportunities to apply AI and advanced machine learning approaches to solve complex business problems. Evaluate alternative data sources and external vendor solutions by defining and driving proof of concept projects to demonstrate the solutions business values. Explore and leverage inhouse, external, and other opensource machine learning software/algorithms. Contribute in enhancing SoFi’s risk model development code base by developing customized Python scripts or packages. Collaborate with Model Risk Management team and Fair Lending team to demonstrate models are developed with high level rigor that satisfy Model Risk Management requirements, Fair Lending requirements, and other regulatory requirements. Spearhead model deployment by collaborating with cross functional teams including Credit, Product, Engineering, and Business Unit. Present model performance and insights to Credit, Risk, and Business Unit leaders. Full-time telecommuting is an option. Requirements: Master’s degree in Statistics, Data Science, or a related quantitative discipline and (5) five years of experience in the job offered or a related occupation Or Bachelor’s degree in Statistics, Data Science, or a related quantitative discipline and (7) seven years of experience in the job offered or a related occupation. Special Skill Requirements: (1) Machine Learning and statistical modeling for supervised and unsupervised learning; (2) Python; (3) Databases and related languages and tools including SQL, NoSQL, and Hive; (4) Statistical Inference (5) Full model development cycle on modern cloud platform including model development, implementation and monitoring; (6) Experience in unsecured loan credit and cashflow underwriting. (7) Familiar with credit bureau data such as Experian, TransUnion or Equifax (8) Experience in model implementation including CICD pipeline and deployment of models to production endpoints. Any suitable combination of education, training and/or experience is acceptable. Full-time telecommuting is an option. Salary: $223,560.00 - $245,916.00 per year. Submit resume with references using the apply button on this posting or by email to: Req.# 1014.40.2 at: ATTN: HR, jobadverts@sofi.org . #LI-DNI Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identit