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Intuit is seeking a Staff Data Scientist on the CK Intelligence team to shape AI strategy and measurement for AI-native experiences. You will lead evaluation, design experiments, and translate early learnings into strategic direction that impacts product roadmaps and business metrics.
You’ll partner with senior leaders to champion rigorous experimentation, develop scalable data models, and enable teams to iterate quickly with evidence-driven decisions.
Company Overview
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 TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe everyone should have the opportunity to prosper. We never stop innovating to make that possible.
CK Intelligence is the team building Credit Karma’s AI products. We are developing AI-native experiences across three pillars: Chat, where members ask anything about their finances; Agents, which complete multi-step work on a member’s behalf; and Insights, which proactively surface what changed and what to do next.
As part of this transformation, we are looking for a Staff Data Scientist to help shape the strategy and measurement of Credit Karma’s next generation of AI capabilities.
This role is ideal for someone who thrives in zero-to-one environments at the intersection of data, experimentation, AI evaluation, storytelling, and business leadership. You will help teams evaluate nascent AI capabilities, identify the strongest signals of member and business value, and translate early learnings into clear strategic direction.
Strategy and Measurement for AI-Native Experiences Identify, evaluate, and size AI use cases against business value, and apply personalization and automation frameworks to shape what gets built. Build and run AI evaluation, including golden datasets and LLM-as-judge calibration, to certify non-deterministic experiences and diagnose where they need to improve.
Zero-to-One Measurement Develop measurement strategies for AI products where established benchmarks do not yet exist. Define leading indicators, learning milestones, success criteria, and the quality, latency, and reliability bars an experience must clear before it reaches members.
Experimentation and Causal Rigor Apply causal inference and counterfactual reasoning to isolate what actually moved a metric. Design and run the experiments and holdouts that resolve whether an AI experience is incremental rather than merely adopted, and own predictive models through their lifecycle.
Strategic Thinking and Business Acumen Frame the right question before any analysis runs, and meaningfully drive AI product strategy. Generate insights and testable hypotheses that alter roadmaps and resource decisions, and define the business metrics and causal levers the business manages to.
Member Lifecycle Intelligence Build a deeper understanding of how members discover, adopt, and return to AI experiences, and which jobs-to-be-done actually get solved. Distinguish experiences that create genuine member value from those that shift where existing activity happens.
Data Products and Decision Governance Build and maintain the data products that CK Intelligence, and its agents, depend on. Prototype the data model, pipeline, and surface, then partner with engineering to harden what sticks, and govern the decision systems between data and member experience.
Agentic Analytics and Delegation Automate the team’s analytical bottlenecks into agentic systems stakeholders run independently. Own the agent context so it inherits the rigor and not just the query, and decide with evidence which analytical work may run without a human in the loop.
Executive-Facing Visualization and Storytelling Develop compelling visualizations, dashboards, and presentations that enable leadership to quickly understand performance, tradeoffs, and emerging opportunities. Bring clarity to complex or incomplete analytical narratives.
Cross-Functional Influence Serve as a trusted data science partner to senior leaders across Product, Engineering, Design, and Marketing. Facilitate alignment through data and create shared understanding of hypotheses, performance drivers, risks, and opportunities.
Thought Leadership and Enablement Champion best practices in experimentation, AI evaluation, measurement, and decision science. Mentor other data scientists and analysts and contribute to a culture of rigorous, data-informed innovation.
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). 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.
San Diego $185,500 - $251,000