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Senior Data Scientist - Flex Pay

San Francisco

Pay
USD 100,000–150,000/yearPlus equity — pay source
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.
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What you’ll work on

Full posting

We are seeking a highly analytical and results-driven Data Scientist to join our buy now pay later (BNPL) sector called Flex Pay.

While this position is ideally based in our San Francisco office on a hybrid basis, we are also open to considering remote candidates.

  • Build and maintain credit and fraud policy simulators

  • Build and deploy statistical models and machine learning algorithms

  • Validate models to identify factors that may affect performance

  • Analyze large structured and unstructured datasets using SQL and Python

  • Work with risk, marketing, product, and engineering on data-driven strategies

From the employer’s posting
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.
While this position is ideally based in our San Francisco office on a hybrid basis, we are also open to considering remote candidates.
Build and maintain credit and fraud policy simulators used to ensure properly functioning systems
Build and deploy statistical models and machine learning algorithms to solve business problems
Validate models to identify factors that may affect model performance.
Analyze large, structured and unstructured datasets using SQL, Python or similar tools.
Collaborate with cross-functional teams including risk, marketing, product, and engineering to define data-driven strategies.
Education & alternatives
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.

Tools in this posting

  • Python
  • SQL
  • Power BI
  • Tableau
  • NumPy
  • pandas
  • PySpark
  • scikit-learn
Source — Tool mentions in context
- 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.
- 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.).
Nice to Have: - Experience with data visualization tools (e.g., Tableau, Power BI). - Experience with AI tools such as Claude
- 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.

Posting record

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Status in our records
Live
First seen by us
Oct 1, 2026 · 28 days ago
Recorded sightings
22
Last seen by us
Oct 29, 2026

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Job description

View original posting ↗

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. 

 

While this position is ideally based in our San Francisco office on a hybrid basis, we are also open to considering remote candidates.

 

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.

Source details

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Pay
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.
Location & working pattern

San Francisco

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. While this position is ideally based in our San Francisco office on a hybrid basis, we are also open to considering remote candidates. What You’ll Do:
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