Fraud AI Scientist - Fintech Consumer Risk Fraud

Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as Turbo Tax, Credit Karma, Quick Books, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Intuit’s Consumer Group, including Turbo Tax and Credit Karma, empowers millions of individuals to take control of their finances. Turbo Tax simplifies tax preparation and enables our customers to file with confidence. By harnessing the power of data and artificial intelligence (AI), we continuously innovate and evolve our consumer offerings to deliver even greater value.

As we expand our primary banking and lending products, Intuit Credit Karma is looking for an innovative, experienced, and hands-on Staff AI Scientist to join our Consumer Risk Data Science team. In this role, you’ll develop cutting-edge credit risk AI/ML fraud models to enable existing and new money movement products. Join a collaborative and inventive team of AI scientists and machine learning engineers where your work will have a direct impact on hundreds of thousands of customers.

• 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.
• Research and implement practical and creative machine learning and statistical approaches suitable for our fast-paced, growing environment.

• Solve hard, meaningful problems giving customers (not fraudsters) access to their hard-earned money alongside fun, smart people.
• Experience professional growth and encourage growth throughout the team.
• Work cross functionally (with executives, engineering, policy & rules, product, analytics, operations and other AI science teams) to ensure efficient and effective use of data science in ways that make an immediate, substantial, and sustainable impact

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location.

To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:

• Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline
• 7-10 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…