Lead Data Scientist at Petal

About Petal and 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 Lead Data Scientist role 

We are working on revolutionizing credit through usage of personal cash flow in underwriting. Achieving this objective requires best in class models that are continuously being improved making the data science function critical for this mission.  These models will support our risk underwriting, acquisition and customer management teams. These models will allow our clients to improve their underwriting, acquisition, and customer management processes.


Key responsibilities:

Develop insights and data visualizations to solve complex problems and communicate ideas to internal stakeholders.
Build predictive models from development through testing and validation for customer acquisition, underwriting and customer management.  Utilize unstructured data in model development.
Extract and analyze data, investigate data integrity, generate metrics and perform ad hoc analysis.
Take accountability and ownership of end to end data science model/score design, development, and delivery.
Provide analytical consulting and thought leadership to stakeholders.
Lead junior teammates and partner with cross functional teams
Research new models and algorithms to improve our credit scoring.
Research new and enhanced model features to improve risk models.
Partner with data engineers to validate & deploy solutions in an efficient, sustainable & usable manner.



Characteristics of a successful candidate:

>5 years experience in data science building and implementing models; B.A. or M.S. degree in a STEM Major (Science, Technology, Engineering, or Math) or work equivalent is required.
Strong knowledge of traditional and machine learning models.
Strong knowledge of R , SQL and Python.
Strong self-management, drive, and organization. 
Ability to multi-task in a fast-paced environment is essential.
Experience in financial services industry
Ability to translate technical concepts to a non-technical audience



Nice-to-haves: 

Management experience
B2B Experience working at a vendor



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