Credit Karma
Staff AI Scientist - Consumer Risk Fraud (Intuit)
Credit Karma, Mountain View, California, us, 94039
Intuit Credit Karma is a mission-driven company focused on championing financial progress for more than 140 million members globally. While best known for pioneering free credit scores, our members turn to us for everything related to their financial goals, including identity monitoring, credit cards, insurance, lending and savings. We now have more than 1,700 employees across offices in Oakland, Charlotte, Culver City, San Diego, London, Bangalore and New York City.
What you’ll do:
Contribute to fraud risk AI science initiatives for new and evolving money product offerings, owning the model lifecycle and driving data strategy across involved teams
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict and detect fraud risk for CK Money and short‑term lending products (e.g., tax refund advances, FNPL, installment loans, single payment loans, early wage access)
Collaborate with credit policy, product and fraud risk teams to align models with business goals and drive actionable lending decisions
Build efficient and reusable data pipelines for feature generation, model development, scoring and reporting using Python, SQL and both commercially available and proprietary ML and AI infrastructures
Deploy models in a production environment in collaboration with other AI scientists and machine learning engineers
Ensure model fairness, interpretability and compliance
Research and implement practical and creative machine learning and statistical approaches suitable for our fast‑paced, growing environment
Minimum Basic Requirement:
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
Authoritative knowledge of Python and SQL
Relevant work experience in fintech fraud risk, with deep understanding of money movement products, banking, lending, and fraud detection data
Relevant work experience in credit risk and/or financial fraud risk, with deep understanding of payment systems, money movement products, banking and lending
Experience with and deep understanding of developing, deploying, monitoring and maintaining a variety of machine learning techniques, including deep learning, tree‑based models, reinforcement learning, clustering, time series, causal analysis and natural language processing
Deep understanding of fraud risk modeling concepts, including fraud score calibration, label bias correction, case disposition logic and network or graph‑based link analysis for identifying organized or collusive fraud patterns
Ability to quickly develop a deep statistical understanding of large, complex datasets
Expertise in designing and building efficient and reusable data pipelines and framework for machine learning models
Strong business problem solving, communication and collaboration skills
Ambitious, results oriented, hardworking, team player, innovator and creative thinker
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, contributing to the company’s external technical visibility and innovation agenda
Preferred Qualifications:
Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.
Work experience with public cloud platforms (especially GCP or AWS) and workflow orchestration tools like Apache Airflow
Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, including pipelines, automated retraining, monitoring and version control
Experience with experimentation design and analysis, including A/B testing and statistical analysis
Benefits and Compensation: Intuit provides a competitive compensation package with a strong pay‑for‑performance rewards approach. The expected base pay range for this position in the Bay Area, California is $205,500 – $278,000. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs.
Equal Employment Opportunity: Credit Karma
is proud to be an Equal Employment Opportunity Employer. We welcome all candidates without regard to race, color, religion, age, marital status, sex (including pregnancy, childbirth, or related medical condition), sexual orientation, gender identity or gender expression, national origin, veteran or military status, disability (physical or mental), genetic information or other protected characteristic. We prohibit discrimination of any kind and operate in compliance with applicable fair chance laws.
Credit Karma is also committed to a diverse and inclusive work environment because it is the right thing to do. We believe such an environment advances long‑term professional growth, creates a robust business, and supports our mission of championing financial progress for everyone.
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What you’ll do:
Contribute to fraud risk AI science initiatives for new and evolving money product offerings, owning the model lifecycle and driving data strategy across involved teams
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict and detect fraud risk for CK Money and short‑term lending products (e.g., tax refund advances, FNPL, installment loans, single payment loans, early wage access)
Collaborate with credit policy, product and fraud risk teams to align models with business goals and drive actionable lending decisions
Build efficient and reusable data pipelines for feature generation, model development, scoring and reporting using Python, SQL and both commercially available and proprietary ML and AI infrastructures
Deploy models in a production environment in collaboration with other AI scientists and machine learning engineers
Ensure model fairness, interpretability and compliance
Research and implement practical and creative machine learning and statistical approaches suitable for our fast‑paced, growing environment
Minimum Basic Requirement:
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
Authoritative knowledge of Python and SQL
Relevant work experience in fintech fraud risk, with deep understanding of money movement products, banking, lending, and fraud detection data
Relevant work experience in credit risk and/or financial fraud risk, with deep understanding of payment systems, money movement products, banking and lending
Experience with and deep understanding of developing, deploying, monitoring and maintaining a variety of machine learning techniques, including deep learning, tree‑based models, reinforcement learning, clustering, time series, causal analysis and natural language processing
Deep understanding of fraud risk modeling concepts, including fraud score calibration, label bias correction, case disposition logic and network or graph‑based link analysis for identifying organized or collusive fraud patterns
Ability to quickly develop a deep statistical understanding of large, complex datasets
Expertise in designing and building efficient and reusable data pipelines and framework for machine learning models
Strong business problem solving, communication and collaboration skills
Ambitious, results oriented, hardworking, team player, innovator and creative thinker
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, contributing to the company’s external technical visibility and innovation agenda
Preferred Qualifications:
Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.
Work experience with public cloud platforms (especially GCP or AWS) and workflow orchestration tools like Apache Airflow
Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, including pipelines, automated retraining, monitoring and version control
Experience with experimentation design and analysis, including A/B testing and statistical analysis
Benefits and Compensation: Intuit provides a competitive compensation package with a strong pay‑for‑performance rewards approach. The expected base pay range for this position in the Bay Area, California is $205,500 – $278,000. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs.
Equal Employment Opportunity: Credit Karma
is proud to be an Equal Employment Opportunity Employer. We welcome all candidates without regard to race, color, religion, age, marital status, sex (including pregnancy, childbirth, or related medical condition), sexual orientation, gender identity or gender expression, national origin, veteran or military status, disability (physical or mental), genetic information or other protected characteristic. We prohibit discrimination of any kind and operate in compliance with applicable fair chance laws.
Credit Karma is also committed to a diverse and inclusive work environment because it is the right thing to do. We believe such an environment advances long‑term professional growth, creates a robust business, and supports our mission of championing financial progress for everyone.
#J-18808-Ljbffr