Upgrade Inc.
Senior Data Scientist - Flex Pay
San Francisco · Senior
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
The bottom of this range ($100,000) is below the Level I prevailing wage of $110,386. An H-1B cannot be filed below the prevailing wage, so an offer at the floor of this band could not be sponsored as posted.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $142,438 would place this position at wage Level II. That figure is within the posted range, and I'd like to target it. This role classifies under "Data Scientists" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Data Scientists (15-2051) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Files H-1B transfers
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- We are seeking a highly analytical and results-driven Data Scientist to join our buy now pay later (BNPL) sector called Flex Pay.
- This role requires a strong foundation in statistics, machine learning, and programming.
- While this position is ideally based in our San Francisco office on a hybrid basis, we are also open to considering remote candidates.
Responsibilities
- Build and maintain credit and fraud policy simulators used to ensure properly functioning systems and identify risk decisioning enhancements.
- Validate models to identify factors that may affect model performance.
- Collaborate with cross-functional teams including risk, marketing, product, and engineering to define data-driven strategies.
- Ability to write documentation and present analysis to people with different levels of expertise (e.g., technical staff, business leads, etc.).
- You will play a key role in building predictive risk models, optimizing offers and pricing, and extracting insights that drive product development, risk mitigation, and customer strategy.
Requirements
- Advanced Degree (MS/PhD) in Data Science, Statistics, Mathematics, Computer Science, Finance, or a related quantitative discipline.
- Strong proficiency in Python (Pandas, Numpy, Scikit-learn) and SQL.
- Proactive, driven, and ability to work in a fast paced environment.
Nice to have
- Experience with data visualization tools (e.g., Tableau, Power BI).
- Experience with AI tools such as Claude
- Experience with data technologies like PySpark.
- Understanding of financial services concepts such as credit scoring, portfolio risk, or customer lifetime value.
- Competitive 401(k) and RRSP program
- Opportunities for professional growth and development
Skills
- Analyze large, structured and unstructured datasets using SQL, Python or similar tools.
Compensation
- Competitive salary and stock option plan
Benefits
- Competitive salary and stock option plan
- Paid coverage of medical, dental and vision insurance
- Paid parental leave
- Health & wellness initiatives
- The compensation range of this position in San Francisco, CA is USD $100,000-$150,000 annually plus equity and benefits.
- Within this range, an individual's base pay will be dependent on a variety of factors, including without limitation, job-related knowledge, skills, education, and experience.
- Build and deploy statistical models and machine learning algorithms to solve business problems in areas like credit risk, fraud detection, pricing, customer segmentation, and marketing attribution.
- Experience and/or strong interest in machine learning techniques (Random Forest, Gradient Boosted Trees, etc.) strongly preferred.
Company info
- About the Role: We are seeking a highly analytical and results-driven Data Scientist to join our buy now pay later (BNPL) sector called Flex Pay.
This listing is sourced directly from Upgrade Inc.'s careers page and normalized into a canonical job model.