Job Description

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.

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 (see more about our compensation and benefits at ). 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.
• Bachelors degree in Data Science, Statistics, Computer Science, or a related field; Masters preferred .

EXTRA -EXTRA

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

While priorities shift based on business needs, a typical day might include:

• 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.

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