Staff Data Scientist - AI Strategy and Evaluation

Intuit; San Diego (CA); On-site; USD 186,000 - 251,000; Full time

Job summary

Intuit’s CK Intelligence team is seeking a Staff Data Scientist to shape the strategy and measurement of Credit Karma’s AI capabilities. You will guide AI evaluation, build golden datasets, and translate learnings into strategic direction for AI-native experiences.

You will design experiments, apply causal inference, and define success metrics for ambitious, ambiguous problems while partnering with senior leadership across Product, Engineering, and Marketing.

Qualifications

• 8+ years of experience in data science, analytics, business intelligence, or a related field.
• Proven track record of shaping strategy and influencing executive decision making through data.
• Experience supporting zero to one products, emerging business models, growth initiatives, or other highly ambiguous problem spaces.
• Experience measuring or evaluating AI, machine learning, or personalization products, including familiarity with evaluation approaches for generative or non-deterministic experiences such as golden datasets, LLM-as-judge, human review, or quality and latency monitoring.
• Strong expertise in experimentation, performance measurement, customer analytics, and causal or decision-oriented analysis.
• Demonstrated ability to define success metrics and learning frameworks for initiatives without established benchmarks.
• Strong business acumen across customer acquisition, engagement, retention, product strategy, and operations.
• Expertise in data visualization tools such as Tableau, Power BI, Looker, or similar platforms.
• Advanced SQL proficiency and experience using Python or R for analysis, modeling, and automation.
• Exceptional storytelling and communication skills, with the ability to craft clear and compelling business narratives from complex or incomplete data.
• Demonstrated ability to lead cross-functional initiatives and deliver impact in ambiguous, fast-moving environments.

Responsibilities

• 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.
• Zero-to-One Measurement: Develop measurement strategies for AI products where established benchmarks do not yet exist.
• Experimentation and Causal Rigor: Apply causal inference and counterfactual reasoning to isolate what actually moved a metric.
• Strategic Thinking and Business Acumen: Frame the right question before any analysis runs, and meaningfully drive AI product strategy.
• 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.
• Data Products and Decision Governance: Build and maintain the data products that CK Intelligence, and its agents, depend on.
• Agentic Analytics and Delegation: Automate the team’s analytical bottlenecks into agentic systems stakeholders run independently.
• Executive-Facing Visualization and Storytelling: Develop compelling visualizations, dashboards, and presentations for leadership.
• Cross-Functional Influence: Serve as a trusted data science partner to senior leaders across Product, Engineering, Design, and Marketing.
• Thought Leadership and Enablement: Champion best practices in experimentation, AI evaluation, measurement, and decision science.

Skills

Data science

Analytics

Business intelligence

Experimentation

Causal/decision analysis

Data visualization

SQL

Python/R

Executive communication

Cross-functional leadership

Education

Bachelor's degree or higher in a relevant field

Tools

Tableau

Power BI

Looker

Job description

Intuit’s CK Intelligence team is seeking a Staff Data Scientist to shape the strategy and measurement of Credit Karma’s AI capabilities. You will guide AI evaluation, build golden datasets, and translate learnings into strategic direction for AI-native experiences.

You will design experiments, apply causal inference, and define success metrics for ambitious, ambiguous problems while partnering with senior leadership across Product, Engineering, and Marketing.