The Intuit Customer Success (ICS) Data Science team is seeking to drive innovation and enhance customer experiences through Intuit's world-class expert services by defining and building the foundational intelligence system that maps the end-to-end expert journey, identifying and quantifying points of friction in the expert workflow, and establishing causal relationships to business outcomes.
Requirements
- Expert proficiency in SQL and Python/R for data analysis, modeling, and pipeline development.
- Deep, hands-on experience translating a business problem into a predictive/prescriptive modeling problem and leading the end-to-end model development lifecycle.
- Advanced knowledge and applied experience with a wide range of Causal Inference methods (including Causal Graph/Causal AI techniques) and advanced statistical methods.
- Experience in AI/ML, Generative AI (GenAI), and LLM integration into analysis/data workflows, including prompt optimization and fine-tuning.
- 7+ years in Data Science, applied Machine Learning, and/or advanced statistical modeling, with a focus on product or customer experience analytics.
- Experience with Behavioral Modeling on clickstream data, Anomaly Detection for friction identification, and Automated Opportunity Sizing models.
Responsibilities
- Strategic Vision & Framework Development
- Strategy to Problem: Demonstrate the ability to turn complex business strategy into well-defined, measurable analytical problems and iteratively self-generate and validate hypotheses to create actionable insights.
- Metric System & Causal Structure: Lead the development and implementation of a tiered metric system that maps the causal relationships between high-level business goals and low-level product health metrics, leveraging Causal AI methods to structure and connect input metrics to outcome metrics.
- Advanced Causal Measurement & Modeling
- Causal Measurement Strategy: Design and implement a durable strategy for measuring the causal impact of expert-facing features, with a primary focus on Customer Serving Time (CST) reduction and ensuring GenAI efficiencies are fully achieved and accurately attributed.
- Model Development & Innovation: Lead the end-to-end development of advanced analytical models, including Behavioral Modeling on clickstream data, Anomaly Detection for friction identification, and Automated Opportunity Sizing models.
- AI Strategy Co-Creation & Guidance: Co-create the Expert Experiences AI strategy in partnership with cross-functional teams.
Other
- 7+ years in Data Science, applied Machine Learning, and/or advanced statistical modeling, with a focus on product or customer experience analytics.
- Education: Bachelor’s or Master's Degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Economics, Operations Research, etc.)
- Strategic Impact: Proven track record of influencing Director and VP-level cross-functional partners, driving strategic decisions, and creating reusable analytical assets or frameworks that scale across business units.
- Communication: Outstanding communication and data storytelling skills, with the ability to articulate complex technical findings to non-technical executive audiences.
- Mentorship: Actively raise the team’s technical knowledge, skill, and engagement by mentoring junior employees, documenting and sharing standards, and participating in technical forums.
