Staff AI Scientist

Intuit Credit Karma is looking for a results-oriented and strategically innovative Staff AI Scientist to lead the evolution of our recommendation engines from static eligibility matching to dynamic, intent-aware personalization. You will architect the systems that determine which financial products are shown to 100M+ members, balancing immediate monetization with long-term member trust.

As the Tech Lead, you will drive the technical vision for our user understanding and recommendation stacks. You will mentor junior scientists, set the standard for experimental rigor, and partner with senior leadership and product teams to define the future of our members’ financial journey.

What you’ll do:

• Responsible for building and scaling machine learning models that identify user intents, financial journey, engagement patterns, as well as lead the evolution of our recommendation and ranking systems across a diverse ecosystem of financial products
• Serve as the primary technical authority for data science teams. Partner with product to define the multi-year roadmap, ensuring technical feasibility for "Big Bet" initiatives, and collaborate with engineering to ensure modeling advances are matched by scalable, low-latency production infrastructure
• Act as a "Force Multiplier" by setting coding and modeling standards, conducting deep-dive reviews, and fostering a culture of scientific excellence across the organization.

What’s great about the role:

• Impact at Scale: Your models will influence the financial journeys of millions of members, balancing immediate conversion with long-term trust and value.
• Strategic Influence: You will play a key role in defining how Credit Karma prioritizes its diverse ecosystem of financial verticals through data-driven frameworks.
• Technical Growth: You will work with one of the richest datasets in fintech to solve complex problems in multi-objective optimization and predictive modeling.

Minimum Basic Requirement:

• MS in Computer Science, Mathematics, Statistics, Physics or a related quantitative discipline
• 7+ years of industrial experience in Machine Learning, with 3 years in a technical lead capacity specifically focused on Ranking, Search, or Recommendation Systems.
• Proven track record of designing and deploying high-scale, multi-stage ranking pipelines in a production environment.
• Exceptional ability to communicate technical complexity to executive leadership and influence stakeholders across product, business and engineering.

Preferred Qualifications:

• Personalization & Ranking: Experience with multi-objective optimization and ranking systems that manage competing business and user goals.
• Lifecycle Modeling: Familiarity with survival analysis, time-series forecasting, or sequence-to-sequence modeling to predict user actions over time.
• Business Acumen: Ability to translate high-level business goals into rigorous mathematical objective functions.
• Communication: Exceptional ability to communicate technical concepts to non-technical stakeholders and drive organizational alignment.