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Employer
About Intuit
Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology
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174 open roles
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Lead Partner Decision Scientist - Credit Karma joins the Partner Decision Science team to serve as a technical bridge between the internal decision-science platform and external data science and credit-risk teams at partner banks and fintech lenders. This role involves designing, building, and optimizing large-scale targeting and approval models to increase conversion and revenue while improving member certainty. The successful candidate will advance the modeling toolkit through feature engineering on consumer credit and bureau data, modern machine learning methods, and generative AI applications. Key responsibilities include collaborating with internal product and engineering teams to move models into production and translating complex technical concepts for non-technical stakeholders. Required skills include expert proficiency in Python and SQL, experience with BigQuery or similar warehouses, and deep knowledge of credit risk analytics, underwriting, and various bureau data sources.
Act as the technical bridge between Credit Karma's platform and partner data science and credit-risk teams.
Design, build, and optimize large-scale targeting and approval models to increase conversion and revenue.
Advance the modeling toolkit through feature engineering on credit data, modern ML methods, and generative AI applications.
Build relationships with external partner teams and coach them on platform capabilities.
Translate partner requirements into technical specifications for internal product and engineering teams.
Communicate complex technical concepts to non-technical stakeholders and executive audiences.
Identify high-impact opportunities across the partner portfolio and drive them through to production.
What we're looking for
MS in Statistics, Mathematics, Computer Science, Economics, Physics, or a related quantitative discipline (or a BS with equivalent applied experience).
At least 5 years of experience in credit-risk analytics, data science, or risk management at a bank, fintech, or credit bureau.
Deep, hands-on understanding of credit data including bureau attributes, risk scores, and alternative data sources.
Expert proficiency in Python and SQL with experience in modern ML frameworks and large-scale data warehouses like BigQuery.
Proven ability to explain complex modeling concepts and connect model performance to business outcomes for non-technical and executive stakeholders.
Exceptional verbal and written communication skills to influence senior audiences in their decision-making.
Experience with targeting modeling, recommendation and ranking, experimentation, and generative AI applications.
Machine Learning
Python
Scala
R
Deep Learning
Big Data
Distributed Computing
Statistical Modeling
Sentiment Analysis
Clustering
Classification
High Performance Computing