below marketmost similar roles pay hereabove market
This role pays more than
60%
of similar roles. Most pay
$167,490–$237,000
— the blue band above.
At the midpoint, this role pays about
$212k
versus about
$202k
for comparable roles.
Based on 240 similar postings.
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
Intuit currently has
255 open roles
on FindRole.
Listed pay typically runs
$202,500–$274,000
across 236 roles with salary data.
Lead Partner Decision Scientist - Credit Karma joins the Partner Decision Science team to serve as a technical bridge between the company's decision-science platform and the data science and credit-risk teams of 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 approval certainty for members. Key responsibilities include performing feature engineering on consumer credit and bureau data, applying modern machine learning methods, and exploring generative AI applications. The successful candidate will use Python, SQL, and BigQuery to translate partner needs into production capabilities. The work focuses on credit-risk analytics, targeting modeling, recommendation, ranking, and experimentation to provide relevant financial recommendations within the Credit Karma Lightbox platform.
Serve 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 partner modeling toolkit using feature engineering, modern ML methods, and generative AI applications.
Coach partner data science and risk teams on the capabilities of the Credit Karma platform.
Translate partner needs into platform capabilities and move models into production with internal engineering and product teams.
Translate complex technical subject matter for executive and non-technical audiences in partner-facing meetings.
Identify high-impact opportunities across the partner portfolio and lead them through to measurable production results.
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).
Approximately 5+ years 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 to non-technical and executive stakeholders and connect model performance to business outcomes.
Exceptional verbal and written communication skills to convey complex ideas and influence senior audiences.
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Deep Learning
Python
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Java
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