The Petal mission

Petal’s mission is to expand access to opportunity, by making responsible, modern financial services available to everyone. Founded in 2016, Petal provides technology-enabled credit cards to consumers who are historically underserved by mainstream providers. 

Petal pioneered automated cash flow underwriting, a transformative new approach to assessing consumer creditworthiness with the potential to expand access to tens of millions of U.S. consumers without credit history, or for whom traditional credit scores do not tell the whole story. Petal pairs this groundbreaking, data-driven underwriting technology with a mobile-first, digitally native product experience designed to help users manage and build credit responsibly. For Petal, it’s a mission as much as it is a business—with a goal to reimagine finance for the next generation of consumers.

At Petal, 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. At Petal, we welcome diverse perspectives from people who think rigorously and aren't afraid to challenge assumptions.

The 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.
• 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 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 success candidate:

• >3 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.

Nice-to-have:

• Experience in financial industry

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