Job Details

We are seeking an exceptionalPrincipal People Data & Analytics Specialistwith deep expertise inartificial intelligence (AI)andmachine learning (ML)to advance our data-driven decision-making capabilities across the enterprise. In this highly impactfulindividual contributorrole, 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 deploypredictive and prescriptive modelsto optimize talent acquisition, performance management, engagement, and retention.
• Implementmachine learning algorithmsto forecast workforce trends (e.g., attrition, career velocity, skill evolution).
• Develop and operationalizenatural language processing (NLP)solutions forsentiment analysisof employee feedback, surveys, and communications.
• Identify and integrateAI-driven toolsthat can be embedded into core People & Places platforms.

Insights & Storytelling

• Translate technical analyses intoclear, actionable insightsfor leaders across the organization.
• Builddata visualizations and dashboardsthat 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 sharebest practices, methods, and tools.
• Act as anAI/ML subject matter expertfor people analytics initiatives.

Innovation & Research

• Stay ahead ofemerging AI, ML, and advanced analytics trendsrelevant to P&P and organizational science.
• Evaluate and pilotnew technologies, frameworks, and algorithmsto 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 atIntuit: Careers | Benefits).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+ yearsof experience in people data, workforce analytics, or related advanced analytics roles.
• Demonstrated expertise inAI and ML, includingpractical implementationof algorithms and models in production environments.
• Proficiency in programming languages such asPythonorR, with strong experience indata wrangling, modeling, and visualization.
• Strong applied experience withpredictive analytics, NLP, and sentiment analysistechniques.
• Ability to work independently inambiguous, fast-paced environmentsand deliver impactful outcomes.
• Exceptionalstorytelling and communication skillsto convey technical findings to non-technical audiences.
• Bachelor's degree in Data Science, Statistics, Computer Science, or a related field;Master's preferred.

EXTRA -EXTRA

What Makes This Role Unique

• Principal-level influencewithout people management — you will be ahands-on expertshaping enterprise analytics strategy.
• Opportunity topush the boundariesof AI and ML applications in HR.
• Direct line of impact onemployee 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.