Lead Partner Decision Scientist - Credit Karma at Intuit

Job description

Credit Karma is looking for a Senior AI Scientist to join our Partner Decision Science team — the group at the center of how the country's largest banks and fintech lenders build, target, and approve on the Credit Karma Lightbox platform. In this role, you will be the technical bridge between Credit Karma's decision-science platform and the data science and credit-risk teams at our partners, turning their objectives into production models that increase conversion and revenue while giving our members greater certainty that they'll be approved for the products they're matched with. This is a highly cross-functional role. You will partner closely with internal business development, engineering, product, and data and analytics teams, as well as with external partner teams that range from hands-on analysts to senior leaders. Success depends as much on your ability to influence and translate across these audiences as it does on your technical depth — we are looking for a scientist who can go deep in the data and models, then clearly explain the "so what" to a room of business and partner stakeholders. You will pair strong machine learning skills with real business acumen, applying techniques that span credit-risk and targeting modeling, recommendation and ranking, experimentation, and — where it adds value — generative AI, all in service of the most relevant, best-timed financial recommendations for our members. Responsibilities • Serve as the technical bridge between Credit Karma's decision-science platform and the data science and credit-risk teams at partner banks and fintech lenders, ensuring partner data and modeling requirements are met end to end. • Design, build, and optimize large-scale targeting and approval models that grow conversion and revenue for Credit Karma and its partners while improving approval certainty for members. • Advance the partner modeling toolkit — feature engineering on consumer credit and bureau data, modern ML methods, and emerging GenAI applications — to lift partner model performance and member relevance. • Build strong relationships with partner data science and risk teams, from individual contributors to managers and directors, and coach them on the capabilities of the Credit Karma platform. • Partner cross-functionally with internal business development, engineering, product, and data and analytics teams to translate partner needs into platform capabilities and move models into production. • Represent the Partner Decision Science team in cross-functional and partner-facing meetings, translating complex technical subject matter for executive and non-technical audiences and advocating for partners inside Credit Karma and for Credit Karma with partners. • Act like an owner: identify high-impact opportunities across the partner portfolio, propose solutions, and see them through to production and measurable results. Qualifications • MS in Statistics, Mathematics, Computer Science, Economics, Physics, or a related quantitative discipline (or a BS with equivalent applied experience). • Approximately 5+ years in credit-risk analytics, data science, or risk management — at a bank, fintech, or credit bureau — with work spanning credit underwriting, model development, or customer valuation. • 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 comfort operating on large-scale data (e.g., BigQuery or a comparable warehouse). • Proven ability to explain complex modeling concepts to non-technical and executive stakeholders and to connect model performance to business outcomes. • Exceptional verbal and written communication skills, with the ability to convey complex ideas and influence senior audiences in their decision-making. • External partner-facing experience is a plus. Footer Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

Requirements

Must-haves

Design, build, and optimize large-scale targeting and approval models that grow conversion and revenue for Credit Karma and its partners while improving approval certainty for members.
Advance the partner modeling toolkit — feature engineering on consumer credit and bureau data, modern ML methods, and emerging GenAI applications — to lift partner model performance and member relevance.
Build strong relationships with partner data science and risk teams, from individual contributors to managers and directors, and coach them on the capabilities of the Credit Karma platform.
Partner cross-functionally with internal business development, engineering, product, and data and analytics teams to translate partner needs into platform capabilities and move models into production.
Act like an owner: identify high-impact opportunities across the partner portfolio, propose solutions, and see them through to production and measurable results.
MS in Statistics, Mathematics, Computer Science, Economics, Physics, or a related quantitative discipline (or a BS with equivalent applied experience).
Approximately 5+ years in credit-risk analytics, data science, or risk management — at a bank, fintech, or credit bureau — with work spanning credit underwriting, model development, or customer valuation.
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 comfort operating on large-scale data (e.g., BigQuery or a comparable warehouse).
Proven ability to explain complex modeling concepts to non-technical and executive stakeholders and to connect model performance to business outcomes.
Exceptional verbal and written communication skills, with the ability to convey complex ideas and influence senior audiences in their decision-making.

Nice-to-haves

External partner-facing experience is a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigomachine learningmlpythonsql

Platform: career-feeds
Effort: medium