Intuit
Staff Credit Risk AI Scientist - Fintech Consumer Risk
Intuit, San Diego, California, United States, 92189
Staff Credit Risk AI Scientist - Fintech Consumer Risk
Join to apply for the Staff Credit Risk AI Scientist - Fintech Consumer Risk role at Intuit.
Intuit is a global financial technology platform serving 100 million customers worldwide, including TurboTax, Credit Karma, QuickBooks, Mailchimp, and more. We focus on empowering consumers to manage finances and are expanding into Consumer Lending.
Overview Intuit Credit Karma seeks an experienced, hands‑on Staff AI Scientist to develop cutting‑edge credit risk AI/ML models for new lending products. You’ll collaborate with AI scientists, ML engineers, and cross‑functional teams to impact hundreds of thousands of customers.
Responsibilities
Contribute to credit risk AI science initiatives for new Money product offerings, owning end‑to‑end model lifecycle and data strategy.
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for short‑term lending products (tax refund advances, BNPL, installment loans, single payment loans, early wage access).
Collaborate with credit policy, product, and fraud risk teams to align models with business goals.
Build efficient, reusable data pipelines for feature generation, model development, scoring, and reporting using Python and SQL.
Deploy models in production with other AI scientists and ML engineers.
Ensure model fairness, interpretability and compliance with FCRA, ECOA, and other regulatory frameworks.
Contribute to the evolution of Intuit’s data and ML infrastructure.
Research and implement practical and creative ML and statistical approaches suitable for a fast‑paced environment.
What’s Great About The Role
Solving hard, meaningful problems while working with smart peers.
Professional growth opportunities and cross‑functional collaboration.
Immediate, substantial, and sustainable impact on consumer risk decisions.
Minimum Qualifications
Advanced degree (Ph.D./MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics, or related discipline.
7–10 years of AI science / machine learning experience.
Expertise in Python and SQL.
Deep understanding of fintech credit risk, payment systems, lending.
Experience with credit bureau, tax and cash flow data in model development.
Proficiency in deploying and monitoring diverse ML techniques (deep learning, tree‑based, reinforcement learning, clustering, time‑series, causal analysis, NLP).
Strong knowledge of credit risk modeling concepts (PD calibration, reject inference, adverse action logic, risk segmentation).
Statistical understanding of large complex datasets.
Expertise in building efficient, reusable data pipelines and ML frameworks.
Excellent problem‑solving, communication, and collaboration skills.
Team player, innovative, results‑oriented.
Experience driving end‑to‑end modeling frameworks across product teams.
Ability to evaluate and integrate emerging AI/ML technologies.
Preferred Qualifications
Experience with TensorFlow, PyTorch, etc.
Experience with GCP or AWS and workflow orchestration (Apache Airflow).
Background in MLOps infrastructure/tooling (Vertex AI, SageMaker).
Experience with experimentation design, A/B testing, statistical analysis.
Compensation Intuit offers a competitive compensation package with cash bonus, equity rewards and benefits. Base salary ranges by location:
Bay Area: $205,500 – $278,000
Southern California: $191,500 – $259,000
New York: $201,500 – $273,000
To maintain pay equity, Intuit conducts regular comparisons across ethnicity and gender categories.
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Intuit is a global financial technology platform serving 100 million customers worldwide, including TurboTax, Credit Karma, QuickBooks, Mailchimp, and more. We focus on empowering consumers to manage finances and are expanding into Consumer Lending.
Overview Intuit Credit Karma seeks an experienced, hands‑on Staff AI Scientist to develop cutting‑edge credit risk AI/ML models for new lending products. You’ll collaborate with AI scientists, ML engineers, and cross‑functional teams to impact hundreds of thousands of customers.
Responsibilities
Contribute to credit risk AI science initiatives for new Money product offerings, owning end‑to‑end model lifecycle and data strategy.
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for short‑term lending products (tax refund advances, BNPL, installment loans, single payment loans, early wage access).
Collaborate with credit policy, product, and fraud risk teams to align models with business goals.
Build efficient, reusable data pipelines for feature generation, model development, scoring, and reporting using Python and SQL.
Deploy models in production with other AI scientists and ML engineers.
Ensure model fairness, interpretability and compliance with FCRA, ECOA, and other regulatory frameworks.
Contribute to the evolution of Intuit’s data and ML infrastructure.
Research and implement practical and creative ML and statistical approaches suitable for a fast‑paced environment.
What’s Great About The Role
Solving hard, meaningful problems while working with smart peers.
Professional growth opportunities and cross‑functional collaboration.
Immediate, substantial, and sustainable impact on consumer risk decisions.
Minimum Qualifications
Advanced degree (Ph.D./MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics, or related discipline.
7–10 years of AI science / machine learning experience.
Expertise in Python and SQL.
Deep understanding of fintech credit risk, payment systems, lending.
Experience with credit bureau, tax and cash flow data in model development.
Proficiency in deploying and monitoring diverse ML techniques (deep learning, tree‑based, reinforcement learning, clustering, time‑series, causal analysis, NLP).
Strong knowledge of credit risk modeling concepts (PD calibration, reject inference, adverse action logic, risk segmentation).
Statistical understanding of large complex datasets.
Expertise in building efficient, reusable data pipelines and ML frameworks.
Excellent problem‑solving, communication, and collaboration skills.
Team player, innovative, results‑oriented.
Experience driving end‑to‑end modeling frameworks across product teams.
Ability to evaluate and integrate emerging AI/ML technologies.
Preferred Qualifications
Experience with TensorFlow, PyTorch, etc.
Experience with GCP or AWS and workflow orchestration (Apache Airflow).
Background in MLOps infrastructure/tooling (Vertex AI, SageMaker).
Experience with experimentation design, A/B testing, statistical analysis.
Compensation Intuit offers a competitive compensation package with cash bonus, equity rewards and benefits. Base salary ranges by location:
Bay Area: $205,500 – $278,000
Southern California: $191,500 – $259,000
New York: $201,500 – $273,000
To maintain pay equity, Intuit conducts regular comparisons across ethnicity and gender categories.
#J-18808-Ljbffr