People Analytics and Intelligence Staff Analyst

Micron Technology•San Jose, CA

About The Position

Strategic, High‑Impact Analytics: Deliver actionable insights across talent acquisition, attrition, performance, learning, diversity, and organizational health. Build and maintain dashboards, visualizations, and data models that support enterprise decision-making. Translate complex business problems into structured analytical approaches. AI, Advanced Analytics, and Innovation: Identify, scope, and support AI/ML use cases in HR (e.g., predictive attrition, skills intelligence, sentiment analysis, workflow automation). Apply AI literacy to evaluate model outputs, ensure responsible usage, and articulate limitations to customers. Partner with data science teams to design, test, and validate AI‑enabled insights. Document risks, assumptions, and ethical considerations for AI in HR, ensuring alignment with governance standards. Experiment with generative AI tools to improve analysis workflows, insights delivery, and automation. Self‑Service Analytics & Enablement: Build intuitive self‑service dashboards and analytics tools that scale across HR. Conduct training, user enablement, and adoption programs. Develop communications, guidance, and materials that increase analytics literacy and usage. Data Governance & Data Quality: Lead data validation, profiling, and quality audits to ensure accuracy and consistency of HR data. Maintain metric definitions, data dictionaries, lineage documentation, and KPI standards. Partner with HRIS, Data Engineering, and Compliance to resolve data issues and improve data pipelines. Embed data quality checkpoints into visualization and data interpretation processes. Consulting & Business Partnership: Act as a trusted analytics advisor to HR leaders and business customers. Deliver custom analytics, deep dives, and problem-solving sessions. Communicate complex insights simply and clearly, tailored to technical and non‑technical audiences.

Requirements

5-8+ years of experience in People Analytics, HR Analytics, or Workforce Insights with strong HR domain knowledge across talent processes and people metrics.
Strong proficiency with BI tools (Power BI, Tableau, Visier, etc.) and advanced skills in SQL, Python, R, or similar tools for analytics.
Experience implementing data governance practices: metric standardization, data lineage, data dictionaries, quality assurance.
Good communication, storytelling, influencing skills and able to lead projects from definition to delivery with high ownership.

Nice To Haves

Hands-on experience in the following AI competencies: Understanding of machine learning basics (predictive modeling, classification, regression, clustering).
Experience applying or evaluating AI tools in an HR or business analytics context.
Ability to interpret AI outputs, explain model insights, and identify risks or biases.
Familiarity with generative AI and analysis workflows guided by user inputs.
Experience with Workday or other HRIS platforms.
Experience operationalizing AI/ML models or AI‑augmented analytics.
Experience developing global self‑service analytics products.
Experience in a multinational, matrixed organization.

Responsibilities

Deliver actionable insights across talent acquisition, attrition, performance, learning, diversity, and organizational health.
Build and maintain dashboards, visualizations, and data models that support enterprise decision-making.
Translate complex business problems into structured analytical approaches.
Identify, scope, and support AI/ML use cases in HR (e.g., predictive attrition, skills intelligence, sentiment analysis, workflow automation).
Apply AI literacy to evaluate model outputs, ensure responsible usage, and articulate limitations to customers.
Partner with data science teams to design, test, and validate AI‑enabled insights.
Document risks, assumptions, and ethical considerations for AI in HR, ensuring alignment with governance standards.
Experiment with generative AI tools to improve analysis workflows, insights delivery, and automation.
Build intuitive self‑service dashboards and analytics tools that scale across HR.
Conduct training, user enablement, and adoption programs.
Develop communications, guidance, and materials that increase analytics literacy and usage.
Lead data validation, profiling, and quality audits to ensure accuracy and consistency of HR data.
Maintain metric definitions, data dictionaries, lineage documentation, and KPI standards.
Partner with HRIS, Data Engineering, and Compliance to resolve data issues and improve data pipelines.
Embed data quality checkpoints into visualization and data interpretation processes.
Act as a trusted analytics advisor to HR leaders and business customers.
Deliver custom analytics, deep dives, and problem-solving sessions.
Communicate complex insights simply and clearly, tailored to technical and non‑technical audiences.