Intuit Principal Data Scientist Growth 

United States, California, San Diego 

383139096

Set Technical Vision and Strategy:

• Define and execute a data science roadmap that drives product funnel optimization and scalable growth initiatives across diverse business areas.
• Utilize rigorous causal inference techniques, advanced statistical modeling, and machine learning to extract actionable insights from complex datasets.

Drive Deep Analytics & Experimentation:

• Develop a comprehensive, end-to-end data view of the customer experience, quickly mastering different areas of the business to identify new opportunities for growth.
• Design, implement, and analyze rapid experiments to validate hypotheses, ensuring every initiative is grounded in data-driven insights and robust causal analysis.

Collaborate Across Functions:

• Partner closely with Product, Engineering, Design, and other cross-functional teams to integrate data insights into actionable product strategies and improvements.
• Support improvements in instrumentation, data quality, and logging to enhance analytical capabilities and drive deeper understanding of customer behavior.

Lead by Example:

• Serve as a technical leader within the Product Growth team, setting the gold standard for analytical rigor and innovative problem-solving.
• Share expertise and best practices in causal inference and advanced analytics, mentoring team members and contributing to the broader growth framework at Intuit.

Operate with Agility and Impact:

• Quickly assimilate and leverage various business metrics and data sources to uncover new insights and propose high-impact hypotheses.
• Balance deep technical work with rapid execution, ensuring insights are translated into effective strategies that deliver tangible results.

Experience & Expertise:

• 10+ years of experience in data science or analytics, with a strong track record in applying advanced analytical methods to drive product and business growth.
• Demonstrated expertise in causal inference techniques, statistical modeling, machine learning, and experimental design.

Technical Proficiency:

• Advanced proficiency in SQL, Python, R, and other analytical tools, with hands-on experience in leveraging data visualization platforms (e.g., Tableau, Power BI) to communicate insights effectively.
• Proven ability to quickly jump into new business areas, mastering the key data and metrics to inform decision-making.

Cross-Functional Collaboration & Leadership:

• Strong communication and storytelling skills, with a history of influencing both technical and non-technical stakeholders through data-driven insights.
• A relentless focus on customer centricity, with deep empathy and a commitment to uncovering opportunities that improve customer experiences.
• An agile, entrepreneurial mindset, capable of balancing long-term strategic initiatives with rapid, iterative experimentation.