Data Scientist - Credit Risk & Fraud Analytics (Fintech)

Upgrade; San Francisco (CA); Hybrid; USD 100,000 - 120,000; Full time

Benefits offered by this job

Stock options

Health insurance

401(k) RRSP program

Flexible PTO

Growth opportunities

Parental leave

Wellness program

Job summary

Upgrade is seeking a highly analytical Data Scientist to join our Flex Pay BNPL team in San Francisco, hybrid on Wednesdays and Thursdays. You will build predictive risk models, optimize offers and pricing, and extract insights to drive product development, risk mitigation, and customer strategy.

You’ll work with cross-functional teams, leverage Python, SQL, and ML techniques, and stay current with fintech data science trends to deliver measurable business impact.

Qualifications

• MS/PhD in a quantitative field such as data science, statistics, mathematics, CS or finance.
• 2+ years in data science/analytics, preferably in financial services.
• Experience with machine learning techniques (Random Forest, Gradient Boosted Trees) preferred.
• Strong Python and SQL proficiency; ability to document and present analyses.

Responsibilities

• Build and maintain credit and fraud policy simulators to support risk decisioning.
• Develop and deploy statistical models and ML algorithms for risk, pricing, and customer analytics.
• Validate models and identify factors impacting performance.
• Analyze large structured and unstructured data using SQL, Python, and related tools.
• Collaborate with risk, marketing, product, and engineering to define data-driven strategies.

Skills

Python

SQL

Data analysis

Documentation

Education

MS/PhD in Data Science, Statistics, Mathematics, Computer Science, Finance, or related quantitative field

Tools

Pandas

NumPy

Scikit-learn

PySpark

Tableau/Power BI

Job description

Upgrade is seeking a highly analytical Data Scientist to join our Flex Pay BNPL team in San Francisco, hybrid on Wednesdays and Thursdays. You will build predictive risk models, optimize offers and pricing, and extract insights to drive product development, risk mitigation, and customer strategy.

You’ll work with cross-functional teams, leverage Python, SQL, and ML techniques, and stay current with fintech data science trends to deliver measurable business impact.