Credit Karma
Staff Credit AI Scientist - Consumer Risk (Intuit)
Credit Karma, San Diego, California, United States, 92189
Overview
Staff Credit AI Scientist – Consumer Risk (Intuit) at Credit Karma. Join a mission‑driven company focused on financial progress for 140+ million members. Lead credit risk AI/ML for new lending products in a collaborative team of scientists and engineers.
Responsibilities
Contribute to credit risk AI science initiatives for new Money product offerings. Own model lifecycle, share success and key results program‑level, and drive data strategy across teams.
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for short‑term lending products (e.g., 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 and product offerings for actionable lending decisions.
Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL, and relevant ML/AI infrastructures.
Deploy models in production in collaboration with other AI scientists and machine learning engineers.
Ensure model fairness, interpretability, and compliance with FCRA, ECOA, and other regulatory frameworks.
Contribute to the evolution of data and machine learning infrastructure within the Intuit ecosystem to improve efficiency and effectiveness of AI science solutions.
Research and implement practical and creative machine learning and statistical approaches suitable for a fast‑paced, growing environment.
Qualifications
Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics, or a related quantitative discipline.
6+ years of work experience in AI Science / Machine Learning and related areas.
Authority knowledge of Python and SQL.
Relevant experience in fintech credit risk with deep understanding of payment systems, money movement products, banking, and lending.
Experience leveraging credit bureau, tax, and cash flow data in credit risk model development.
Experience with diverse ML techniques: deep learning, tree‑based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.
Deep understanding of credit risk modeling concepts: PD calibration, reject inference, adverse action logic, and risk segmentation.
Strong business problem solving, communication, and collaboration skills.
Proven experience defining and driving end‑to‑end modeling frameworks, methodologies, or best practices across multiple product teams or domains.
Demonstrated ability to evaluate and integrate emerging AI/ML technologies and contribute to external technical visibility and innovation agenda.
Preferred Qualifications
Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.
Experience with public cloud platforms (GCP or AWS) and workflow orchestration tools like Apache Airflow.
Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, pipelines, automated retraining, monitoring, and version control.
Experience with experimentation design and analysis, including A/B testing and statistical analysis.
Benefits & Compensation Competitive compensation with base pay range $191,500‑$259,000 in San Diego. Eligible for cash bonus, equity rewards, and benefits. Pay determined by job‑related knowledge, skills, experience, and work location. Intuit conducts regular comparisons across categories of ethnicity and gender to ensure fair pay.
Equal Employment Opportunity Credit Karma is a proud Equal Employment Opportunity Employer. We welcome all candidates without regard to race, color, religion, age, marital status, sex, gender identity, national origin, veteran or military status, disability, genetic information, or other protected characteristic. We prohibit discrimination of any kind and operate in compliance with applicable fair chance laws.
Privacy Credit Karma is strongly committed to protecting personal data. Please review our privacy policies: US Job Applicant Privacy Notice, UK Job Applicant Privacy Notice.
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Responsibilities
Contribute to credit risk AI science initiatives for new Money product offerings. Own model lifecycle, share success and key results program‑level, and drive data strategy across teams.
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for short‑term lending products (e.g., 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 and product offerings for actionable lending decisions.
Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL, and relevant ML/AI infrastructures.
Deploy models in production in collaboration with other AI scientists and machine learning engineers.
Ensure model fairness, interpretability, and compliance with FCRA, ECOA, and other regulatory frameworks.
Contribute to the evolution of data and machine learning infrastructure within the Intuit ecosystem to improve efficiency and effectiveness of AI science solutions.
Research and implement practical and creative machine learning and statistical approaches suitable for a fast‑paced, growing environment.
Qualifications
Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics, or a related quantitative discipline.
6+ years of work experience in AI Science / Machine Learning and related areas.
Authority knowledge of Python and SQL.
Relevant experience in fintech credit risk with deep understanding of payment systems, money movement products, banking, and lending.
Experience leveraging credit bureau, tax, and cash flow data in credit risk model development.
Experience with diverse ML techniques: deep learning, tree‑based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.
Deep understanding of credit risk modeling concepts: PD calibration, reject inference, adverse action logic, and risk segmentation.
Strong business problem solving, communication, and collaboration skills.
Proven experience defining and driving end‑to‑end modeling frameworks, methodologies, or best practices across multiple product teams or domains.
Demonstrated ability to evaluate and integrate emerging AI/ML technologies and contribute to external technical visibility and innovation agenda.
Preferred Qualifications
Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.
Experience with public cloud platforms (GCP or AWS) and workflow orchestration tools like Apache Airflow.
Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, pipelines, automated retraining, monitoring, and version control.
Experience with experimentation design and analysis, including A/B testing and statistical analysis.
Benefits & Compensation Competitive compensation with base pay range $191,500‑$259,000 in San Diego. Eligible for cash bonus, equity rewards, and benefits. Pay determined by job‑related knowledge, skills, experience, and work location. Intuit conducts regular comparisons across categories of ethnicity and gender to ensure fair pay.
Equal Employment Opportunity Credit Karma is a proud Equal Employment Opportunity Employer. We welcome all candidates without regard to race, color, religion, age, marital status, sex, gender identity, national origin, veteran or military status, disability, genetic information, or other protected characteristic. We prohibit discrimination of any kind and operate in compliance with applicable fair chance laws.
Privacy Credit Karma is strongly committed to protecting personal data. Please review our privacy policies: US Job Applicant Privacy Notice, UK Job Applicant Privacy Notice.
#J-18808-Ljbffr