Intuit is seeking to solve the problem of unified measurement frameworks and analytics excellence across global teams, particularly with the integration of emerging AI capabilities such as Generative AI (GenAI) and agentic workflows.
Requirements
- Proven expertise in statistical analysis, experimentation design, and causal inference techniques.
- Strong programming skills in Python or R, with proficiency in SQL (Hive/Presto/BigQuery experience preferred).
- Hands-on experience designing evaluation and measurement frameworks for Generative AI and agentic workflows, including conversational AI, AI assistants, and autonomous task orchestration.
- Experience with data science tools and technologies, including machine learning, deep learning, and natural language processing.
- Experience with cloud-based data platforms, including AWS, GCP, or Azure.
- Experience with data visualization tools, including Tableau, Power BI, or D3.js.
- Experience with agile development methodologies, including Scrum or Kanban.
Responsibilities
- Strategic Alignment with Leadership: Collaborate with product, platform, and engineering leaders to align analytics priorities with platform goals, ensuring data-driven decisions inform roadmaps and investments.
- Unified KPI Framework: Lead the definition, consolidation, and governance of key performance indicators (KPIs) across platform workstreams, enabling consistent and transparent measurement of impact.
- Oversight of Global Analytics Execution: Provide technical and strategic oversight of global analytics teams, ensuring high-quality, timely, and aligned delivery of measurement and analytics initiatives.
- End-to-End Measurement Leadership: Design and implement scalable, durable measurement frameworks to evaluate platform adoption, performance, and long-term business impact.
- GenAI and Agentic Workflow Evaluation: Develop and lead measurement and evaluation frameworks for Generative AI systems and agentic workflows, including GenAI-powered digital assistants, retrieval-augmented generation (RAG), and autonomous task execution.
- Experimentation and Advanced Methods: Guide experiment design and advanced analytical methods to evaluate platform enhancements, including causal inference techniques, attribution frameworks, and robust A/B testing.
- Data Stewardship and Best Practices: Champion sustainable practices in data quality, reporting, and documentation, ensuring long-term maintainability and scalability of analytics infrastructure.
Other
- Advanced degree (MS/PhD) in Statistics, Computer Science, Economics, Mathematics, or a related quantitative field.
- 10+ years of combined academic and industry experience applying scientific methods to real-world, large-scale data problems.
- Excellent communication skills with the ability to influence and collaborate effectively with senior leadership and cross-functional partners.
- Strong business acumen and ability to translate ambiguous questions into clear analytical frameworks, success metrics, and actionable insights.
- Ability to travel to other Intuit locations, including India, as needed.
