About Prism Data
Prism Data is leading the future of cash flow underwriting, which directly addresses the problems faced by millions of Americans who cannot access fairly priced, mainstream credit products through legacy (credit report-based) underwriting. Prism’s infrastructure and API platform analyzes and risk-scores consumers based upon their banking transactional data - enabling banks, fintech lenders, insurers, and others to have a more holistic, real-time view in how consumers earn, save, and spend - so they can serve more customers, build better products, and make smarter risk-based decisions.
Prism was launched in 2021 by Petal, which pioneered the use of automated cash flow underwriting in consumer credit over 6 years ago, as a means of providing consumers, especially those underserved by the mainstream financial system, access to safe and affordable credit.
Prism has emerged from its successful 2021 private beta. We’re building out our first "core team" to commercialize the solution and expand access to businesses broadly.
We’re looking for people with kindness, positivity, and integrity. You’re encouraged to apply even if your experience doesn’t precisely match the job description. Your skills and potential will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. We welcome diverse perspectives from people who think rigorously and aren’t afraid to challenge assumptions.
The Data Science, Intern role
Prism is working on helping to turn consumer banking history into financial insights. Achieving this objective requires best in class models that are continuously being improved, making the data science function critical for this mission. In this role, you will aid in the development of models and conduct research to support the Data Science team.
Key responsibilities:
- Develop insights and data visualizations to solve complex problems and communicate ideas to internal stakeholders.
- Extract and analyze data, investigate data integrity, generate metrics and perform ad hoc analysis.
- Explore and test new data sources to improve our risk and marketing models.
- Research new models, algorithms, and enhanced model features to improve our credit scoring and risk models.
- Partner with data engineers to validate and deploy solutions in an efficient, sustainable and usable manner.
Characteristics of a successful candidate:
- Progress towards a degree in a STEM Major (Science, Technology, Engineering, or Math)
- Strong knowledge of statistical and/or machine learning techniques OR strong knowledge of Python (strong SQL is a plus!)
Nice to haves:
- Strong preference to rising Seniors or candidates working toward MA/MS/PhD
We are an equal opportunity employer, and we are committed to building a team culture that celebrates diversity and inclusion. We’re proud to be different, together.
Petal provides standard ranges in order to be compliant with local legislation as well as to provide greater transparency to candidates. The compensation information provided here is based on a good faith estimate at the time of this job posting.
This role has a rate of $7,000 per month. Ranges are based on function, level, and office location, and are benchmarked against similar stage companies. Exact compensation amounts are determined by multiple factors including but not limited to skill set, level of experience, and office location, and may vary above or below from the amounts listed above.
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