Risk Data Scientist (Remote optional)
New York, NY /
The Petal mission
Petal’s mission is to bring financial opportunity and innovation to everyone.
We're pioneering a new approach to credit, by analyzing an applicant’s banking history, in addition to credit history, to determine their creditworthiness. We call this technology a Cash Score — and it takes into account income, spending, and savings. It’s currently helping thousands of people qualify for credit at better rates, even if they’ve never had it before.
We bring the same ingenuity to our credit card products. Our simple and intuitive app gives members access to credit score tracking, budgeting tools, subscription management, and automated payment options—everything they need to make financial progress.
Now more than ever, Americans need help improving their credit safely, responsibly, and affordably. If this sounds like something you’d like to be a part of, apply now, and let’s change this trillion-dollar industry together.
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.
- 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.
- Experience in financial industry
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