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Credit Genie is looking to solve challenging Machine Learning and Data Science problems in the consumer risk domain to drive results and maintain methodological rigor. The company aims to design and implement next-generation Risk models for underwriting, fraud prevention, and collections, which are central to their business and directly impact customers.

Requirements

• 8+ years of hands-on experience in machine learning, data science, or advanced analytics
• Deep understanding of machine learning algorithms, statistical modeling, and data analysis techniques
• Strong problem-solving abilities, attention to detail, and a data-driven mindset
• Proficiency in Python and common ML/data libraries (NumPy, pandas, scikit-learn, XGBoost, etc.)
• Experience with SQL and data platforms such as Snowflake, Databricks, and Tableau
• an advanced degree is preferred
• design and execute, and evaluate new data acquisition processes as well as A/B tests and other experiments

Responsibilities

• Set the company’s Risk Machine Learning roadmap in collaboration with our cross functional partners
• Own the end-to-end design and development of ML solutions that power our products’ risk decisioning, driving both optimized risk outcomes and an exceptional customer experience
• Work with a growing team of AI/ML experts on the design and implementation of new Risk ML and feature engineering infrastructure
• Partner cross-functionally with Product, Analytics, Engineering, and business teams to generate actionable insights and build data-driven models that drive business impact
• Set and maintain the highest methodological standards for Data Science across the company
• Solve problems that have no clear existing solution and directly impact our customers
• design and implement our company’s next generation of Risk models that will have a vast impact across underwriting, fraud prevention and collections

Other

• A Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical audiences
• Our expectation is that employees are in the office five days a week, allowing for optimal collaboration, inclusivity, and productivity.
• Flexible PTO
• If you require any accommodations to participate in our recruitment process, please inform us of your needs when we contact you to schedule an interview.