Senior Staff AI Scientist

Overview

Intuit Credit Karma is looking for a results-oriented and strategically innovative Senior 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.

Responsibilities

• Lead the design and evolution of ML models that understand user intent, financial journeys, and engagement patterns, powering recommendation and ranking systems across Intuit Credit Karma's financial product ecosystem.

• Serve as the primary technical authority for AI Science, partnering with product to define the multi-year roadmap and collaborating with engineering to ensure models are matched by scalable, low-latency production infrastructure.

• Act as a force multiplier — setting modeling and coding standards, conducting deep-dive reviews, and building a culture of scientific rigor across the organization.

• Partner across the organization to identify high-impact opportunities to leverage Intuit Credit Karma's rich dataset for Personal Finance personalization, targeting, approval odds, and marketing optimization.

• Drive revenue growth through disruptive and continuous improvements in targeting, feature engineering, user profiles, and personalization models.

• Represent AI Science in executive and business reviews, translating complex technical work into clear business impact.

• Represent Intuit Credit Karma externally — at conferences, speaking engagements, and meetups — as a thought leader and talent magnet.

• Participate in research on frontier areas including deep learning, recommender systems, multi-objective optimization, and financial AI.

• Lead and mentor a high-performing AI Science team working on large-scale projects with direct member and business impact.

Qualifications

• 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.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may 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 (https://www.intuit.com/careers/benefits/full-time-employees/) ). 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:

Oakland $226,000 - $306,000

EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.