Advance Intuit's data-driven decision-making capabilities across the enterprise by designing, developing, and implementing AI-powered analytics solutions that drive insights into the employee lifecycle, workforce trends, and organizational health.
Requirements
- 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.
- Experience in people data, workforce analytics, or related advanced analytics roles.
- Translate technical analyses into clear, actionable insights for leaders across the organization.
- Build data visualizations and dashboards that make complex analytics approachable and compelling.
Responsibilities
- 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.
- Build or refine a machine learning pipeline in Python or R, train/test models, and validate their performance against real-world datasets.
- 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.
- 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.
- 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.
Other
- Principal-level influence without people management — you will be a hands-on expert shaping enterprise analytics strategy.
- Exceptional storytelling and communication skills to convey technical findings to non-technical audiences.
- Partner with People & Places stakeholders to ensure solutions align with business priorities.
- 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.
