Intuit is looking to solve the problem of credit risk and fraud detection in their primary banking and lending products, including TurboTax and Credit Karma, by developing cutting-edge credit risk AI/ML fraud models.
Requirements
- Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline
- 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 but not limited to, 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.
- Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.
Responsibilities
- Contribute to the fraud risk AI science initiatives for the new and evolving Money product offerings, including complete hands-on ownership of the model lifecycle, sharing ownership of success and key results at the program-level, and driving the data strategy across all involved teams.
- Design, build, deploy, evaluate, defend, and monitor machine learning models to predict and detect fraud risk for our primary banking product (CK Money) and various short-term lending products (e.g., tax refund advances, FNPL, installment loans, single payment loans, and early wage access)
- Collaborate with credit policy, product and fraud risk teams to ensure models align with business goals and product offering to 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 Machine Learning 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
- Contribute to the evolution of our data and machine learning infrastructure within the Intuit ecosystem to improve efficiency and effectiveness of AI science solutions.
Other
- Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline
- 3-6 years of work experience in AI Science / Machine Learning and related areas
- Strong business problem solving, communication and collaboration skills
- Ambitious, results oriented, hardworking, team player, innovator and creative thinker
- Ability to quickly develop a deep statistical understanding of large, complex datasets
