Zip is looking to solve complex business problems in credit and fraud risk, customer experience, marketing, and more, by developing best-in-class models that have a meaningful impact across the company.
Requirements
- Experience with credit and/or fraud risk
- Experience working with cashflow data (e.g., Plaid, MX, Finicity), particularly in risk modeling, is a strong plus
- Demonstrated proficiency with AI/ML in financial services; risk modeling experience a plus
- Experience implementing models in production
- Proficiency with Python and SQL
- Hands-on experience with Spark/PySpark
- Proficiency with AI architectures/platforms/tooling (e.g., neural networks, GenAI)
Responsibilities
- Own the model lifecycle end-to-end; develop, validate, and deploy AI/ML solutions to complex business problems, with an emphasis on credit and fraud risk models
- Clearly communicate modeling objectives, assumptions, limitations, and performance considerations findings to stakeholders across the business
- Explore and validate data sources, including ad hoc profiling and integrity checks, to support modeling efforts
- Ensure rigorous documentation and clean, maintainable code
- Clearly articulate modeling objectives, assumptions, limitations, and performance considerations
- Adapt to evolving tools and modeling techniques (e.g., GenAI) with agility, and stay ahead of the curve through self-driven learning
- Collaborate with ML engineers to deploy scalable and robust solutions
Other
- Advanced degree (Masters or PhD) in a quantitative field (e.g., Mathematics, Physics, Social Science, Computer Science)
- 5+ years of experience in Data Science
- 2+ years of experience in Financial Services
- Self-starter mentality with strong problem-solving and research skills
- Ability to thrive in a fast-paced, multi-tasking environment
