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- San Francisco, CA
- 8 days ago
- $100,000–$150,000 / year
Senior Data Scientist - Flex Pay.
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Senior Data Scientist - Flex Pay: our view in 3 lines...
- The Role:This role is for a senior data scientist working in buy now pay later products and risk decisioning.
- The Person:The person will build and deploy predictive risk, fraud, pricing, segmentation, and marketing attribution models, maintain policy simulators, validate model performance, and work with risk, marketing, product, and engineering teams.
- Requirements:The ideal candidate has an advanced degree and 3-5+ years of hands-on experience in a data science or analytics role, with strong proficiency in Python, Pandas, Numpy, Scikit-learn, SQL, machine learning techniques, Tableau, Power BI, and PySpark.
About the role
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.
- 3-5+ 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-$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.

