Senior Talent Insight Analyst

Senior Talent Insight Analyst

As the Senior Talent Insight Analyst you will be hands-on, detail-oriented lead, advancing Symbotic's end-to-end people's analytics, employee listening, and workforce intelligence ecosystem, leveraging AI and advanced analytics to drive actionable business insights.

You will bring deep expertise in statistical analysis, psychometrics, and workforce analytics with emerging AI and machine learning capabilities to transform how the organization understands, predicts, and acts on workforce trends. The Talent Analytics & AI Lead will play a critical role in building AI-enabled decision systems, advancing the HR data lake on Google Cloud Platform (GCP), and scaling insight generation across HR and the enterprise. The position reports to the Director, Talent Analytics & HR Transformation.

The Human Resources organization is responsible for recruitment, administration, compensation, benefits, training & development, performance management, and employee relations.

Employee Listening & 360 Assessment Programs

• Instrument Design: Design enterprise-wide survey, listening, and assessment strategies, incorporating psychometric rigor (validity, reliability, scale construction) while leveraging AI to enhance insight depth and speed.
• Program Management: Lead end-to-end survey and assessment of program administration, from vendor coordination to report interpretation.
• Subject Matter Expertise: Continuously evaluate and recommend modern listening technologies and AI capabilities aligned to organizational maturity and needs.

Workforce Analytics & Predictive Modeling

• Reporting: Deliver standardized reporting on workforce metrics (headcount, movement, attrition, recruiting pipelines).
• Forecasting & Modeling: Build flight-risk and predictive turnover models; partner with Finance on workforce capacity and budget planning. Design AI-enabled dashboards and tools that proactively surface insights, risks, and recommendations (not just report metrics).
• Data Integration: Connect survey, assessment, and HRIS data to map engagement drivers and retention risks.
• Success Metrics: Measure and track the impact of talent initiatives; provide data-driven recommendations for continuous improvement.

Data Lake Stewardship & Governance

• Engineering Partner: Partner with Cloud Engineering on the GCP HR data lake to define metrics, requirements, and use cases.
• Data Quality & Security: Uphold strict data privacy, security, and ethical AI practices, including appropriate PII protection and access controls. Ensure high standards of data quality, integrity, and validation across all data pipelines.

Consultative Storytelling & Business Decision Enablement

• Executive Insights: Translate business questions into appropriate analytical methods, synthesize complex data into clear, actionable narratives and dashboards for executive leaders. Leverage AI tools to accelerate insight generation and scale access to workforce intelligence across HR and business leaders.
• HR & Business Leader Enablement: Enable self-service and AI-assisted insights, improving decision quality and speed. Act as a trusted advisor to HR and business leaders, embedding analytics and AI into core decision-making processes.

What you'll need

Education & Experience

• Education: Bachelor's degree required; Master's or higher in Industrial/Organizational (I/O) Psychology (or related field with statistics curriculum).
• Experience: Minimum 5 years in people's analytics or a corporate HR/Talent data role (graduate studies/internships count). Demonstrated experience applying advanced analytics and/or AI techniques to business problems.

Technical Skills

• Languages: Strong proficiency in SQL and either Python or R.
• Data Platforms: Working knowledge of Cloud Data Platforms (GCP preferred, AWS/Azure acceptable) to write queries and validate data.
• Visualization: Proficiency in Tableau, Looker, or equivalent BI tools.
• Methodologies: Expertise in psychometrics, sampling design, descriptive/inferential statistics, and regression. Experience with machine learning, predictive modeling, and/or NLP techniques.

Key Competencies

• Exceptional attention to detail, project management, and data integrity.
• Strong consultative and critical thinking skills—ability to turn ambiguous business problems into structured analytics.
• Excellent interpersonal and communication skills across technical and non-technical teams.

Our Environment

• Up to 10% of travel may be required. Employees must have a valid driver's license and the ability to drive and/or fly to client and other customer locations.
• The employee is responsible for owning a credit card and managing expenses personally to be reimbursed on a bi-weekly basis.
• Remote Opportunity