Credit Genie is looking to solve hard Data Science and analytics problems and drive results in risk optimization strategies for underwriting, fraud prevention, and collections.
Requirements
8+ years of experience analyzing data using SQL or Python. Proficiency in Python for data processing and modeling is preferred
Proven ability to design, execute, and interpret experiments (e.g. A/B testing or causal analysis) to measure impact and inform risk strategy
Experience with SQL and data platforms such as Snowflake, Databricks, and Tableau
Responsibilities
Leverage advanced analytics and machine learning models to optimize Credit Genie’s risk strategies across credit, fraud, and collections
Own the development and delivery of risk insights, driving data-informed decisions that minimize losses while enabling sustainable business growth
Monitor and analyze key risk KPIs, identify emerging loss trends, and propose strategy enhancements to continuously improve approval and portfolio performance
Collaborate cross-functionally with Product, Engineering, Data, and Machine Learning teams to align on shared objectives, provide strategic insights, and deliver actionable solutions
Act as a strategic risk advisor to business stakeholders, translating complex analyses into clear, high-impact recommendations
Tackle ambiguous, high-impact problems with creativity and analytical rigor, developing novel solutions that directly improve customer experience and portfolio outcomes
Design, execute, and evaluate experiments to drive continuous learning and improvement in our risk optimization processes
Other
A Bachelor’s degree in in Statistics, Mathematics, Business, Economics, or related fields; an advanced degree is preferred
Hands-on experience in risk strategy within payments, lending, banking, or financial institutions is a plus
Exceptional problem-solving abilities, analytical rigor, and the ability to translate complex findings into actionable insights for non-technical audiences
Strong organizational skills with the ability to manage multiple projects in a fast-paced environment and meet tight deadlines
Our expectation is that employees are in the office five days a week, allowing for optimal collaboration, inclusivity, and productivity.
