SECTION I · THE BRIEF
Brief #04595Updated 29 SEP 2026SAN FRANCISCOGreenhouseSAN FRANCISCO
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Data Scientist - Flex Pay

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Location
San Francisco
Company size
1,000–2,000
Posted
Today
Via
Greenhouse
Section II · Full ProfileFree with an account
  • 01Comp band & equity packageLocked
  • 02Seniority & experience requirementsLocked
  • 03Interview process & rubricLocked
  • 04Hiring manager & team contextLocked
  • 05Growth trajectory in this roleLocked
  • 06Offer & decision timelineLocked

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Data Scientist - Flex Pay

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Job title
Data Scientist - Flex Pay
Job location
San Francisco
Job description

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. 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. This role requires a strong foundation in statistics, machine learning, and programming. 


This position is based in our San Francisco office in a hybrid capacity, specifically on Wednesdays and Thursdays.


What You’ll Do: 

  • Build and maintain credit and fraud policy simulators used to ensure properly functioning systems and identify risk decisioning enhancements. 
  • 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.
  • Validate models to identify factors that may affect model performance.
  • Analyze large, structured and unstructured datasets using SQL, Python or similar tools.
  • Stay up to date with the latest trends and technologies in data science and fintech, actively research new tools and techniques available for model development.
  • Collaborate with cross-functional teams including risk, marketing, product, and engineering to define data-driven strategies.


What We Look For:

  • Advanced Degree (MS/PhD) in Data Science, Statistics, Mathematics, Computer Science, Finance, or a related quantitative discipline.
  • 2 years of hands-on experience in a data science or analytics role, preferably in financial services. 
  • Experience and/or strong interest in machine learning techniques (Random Forest, Gradient Boosted Trees, etc.) strongly preferred.
  • Strong proficiency in Python (Pandas, Numpy, Scikit-learn) and SQL.
  • Ability to write documentation and present analysis to people with different levels of expertise (e.g., technical staff, business leads, etc.).
  • 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.

 

What We Offer You: 

  • Competitive salary and stock option plan
  • Paid coverage of medical, dental and vision insurance 
  • Competitive 401(k) and RRSP program  
  • Flexible PTO
  • Opportunities for professional growth and development  
  • Paid parental leave
  • Health & wellness initiatives


The compensation range of this position in San Francisco, CA is USD $100,000-$120,000 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.

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Upgrade headquarters

San Francisco, CA

Company size

1,000–2,000 employees

Founded

2016

Total raised

$1,002,000,000

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