Principal - Data Analyst (People) - Intuit : Job Details

Overview

We are seeking an exceptional Principal People Data & Analytics Specialist with deep expertise in artificial intelligence (AI) and machine learning (ML) to advance our data-driven decision-making capabilities across the enterprise. In this highly impactful individual contributor role, you will design, develop, and implement AI-powered analytics solutions that drive insights into the employee lifecycle, workforce trends, and organizational health. You will work hands-on with advanced analytics methods, translating complex data into compelling narratives that influence leaders and shape talent strategies.

Responsibilities

• AI/ML Analytics Development
• Design, build, and deploy predictive and prescriptive models to optimize talent acquisition, performance management, engagement, and retention.
• Implement machine learning algorithms to forecast workforce trends (e.g., attrition, career velocity, skill evolution).
• Develop and operationalize natural language processing (NLP) solutions for sentiment analysis of employee feedback, surveys, and communications.
• Identify and integrate AI-driven tools that can be embedded into core People & Places platforms.
• Insights & Storytelling
• Translate technical analyses into clear, actionable insights for leaders across the organization.
• Build data visualizations and dashboards that make complex analytics approachable and compelling.
• Partner with People & Places stakeholders to ensure solutions align with business priorities.
• Collaboration & Influence
• Work closely with P&P, business leaders, and technology partners to define analytical requirements.
• Collaborate with other analytics teams to share best practices, methods, and tools.
• Act as an AI/ML subject matter expert for people analytics initiatives.
• Innovation & Research
• Stay ahead of emerging AI, ML, and advanced analytics trends relevant to P&P and organizational science.
• Evaluate and pilot new technologies, frameworks, and algorithms to enhance insights.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is:

Bay Area California $216,000 - $292,500

This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs. Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

• 8+ years of experience in people data, workforce analytics, or related advanced analytics roles.
• Demonstrated expertise in AI and ML, including practical implementation of algorithms and models in production environments.
• Proficiency in programming languages such as Python or R, with strong experience in data wrangling, modeling, and visualization
• Strong applied experience with predictive analytics, NLP, and sentiment analysis techniques.
• Ability to work independently in ambiguous, fast-paced environments and deliver impactful outcomes.
• Exceptional storytelling and communication skills to convey technical findings to non-technical audiences.
• Bachelor's degree in Data Science, Statistics, Computer Science, or a related field; Master's preferred

What Makes This Role Unique

• Principal-level influence without people management — you will be a hands-on expert shaping enterprise analytics strategy.
• Opportunity to push the boundaries of AI and ML applications in HR.
• Direct line of impact on employee experience, talent outcomes, and organizational performance

Typical Day in This Role

• Morning – Review updates to active AI/ML models and dashboards, investigate anomalies in predictive analytics outputs, and respond to questions from HR and business stakeholders about data insights.
• Late Morning – Conduct exploratory data analysis for a new project, such as predicting skill gaps for critical roles or modeling attrition risk in a specific business unit.
• Midday – Join a working session with cross-functional partners to refine model requirements or define data sources for an upcoming AI-powered engagement analysis.
• Afternoon – Build or refine a machine learning pipeline in Python or R, train/test models, and validate their performance against real-world datasets.
• Late Afternoon – Prepare a compelling visualization or narrative to present findings to leadership, ensuring technical results are translated into clear business implications.
• End of Day – Research new AI techniques or tools (e.g., transformer models for sentiment analysis) and consider how they could be applied to future people analytics projects.