Leave of Absence Analyst - HROP - AMS Corporate Functions - HR San Jose Regular
Listed on 2026-02-06
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HR/Recruitment
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IT/Tech
Data Analyst
Overview
About the Team
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The Leave of Absence Analyst is responsible for auditing, analyzing, and visualizing leave-of-absence data (e.g., sick leave, parental leave, medical leave, unpaid leave) across the organization. By identifying trends, anomalies, and root causes of leave patterns, the role provides data-driven insights to optimize LOA policies, reduce excessive leave risks, improve workforce scheduling efficiency, and enhance employee well-being. This role collaborates closely with HR business partners, payroll teams, and department managers to align data analysis with business goals and ensure compliance with labor laws (e.g., FMLA in the U.S., statutory leave regulations in the markets).
- Gather end-to-end LOA data from multiple sources (HRIS systems like Workday/SAP Success Factors, payroll platforms, leave request portals, and manual records).
- Ensure data accuracy per payroll cycle; monitor data quality over time and troubleshoot data discrepancies with cross-functional teams (e.g., mismatches between leave requests and payroll deductions).
- Ensure data completeness and consistency through regular data cleaning (e.g., resolving duplicate entries, standardizing leave types, validating date formats) and establish data governance rules (e.g., defining LOA data metrics, updating data dictionaries).
- Conduct descriptive, diagnostic, and predictive analysis on LOA data.
- Descriptive:
Track key LOA metrics (e.g., total LOA cases per quarter, average leave duration by type, department-wise leave rate, approval/rejection rate). - Diagnostic:
Investigate anomalies (e.g., sudden spikes in medical leave in a specific team) and identify root causes (e.g., workplace stress, seasonal illnesses, policy gaps). - Predictive:
Forecast future leave demand (e.g., peak parental leave periods, Q4 sick leave trends) to support workforce planning.
- Descriptive:
- Analyze LOA impact on business operations (e.g., project delays due to key employee leave) and quantify associated costs (e.g., payroll for paid leave, hiring temporary staff).
- Develop regular (weekly/monthly/quarterly) LOA reports and dashboards for stakeholders (HR leaders, department managers, executives) using tools like Tableau, Power BI, Excel, or SQL.
- Translate complex data insights into clear, actionable recommendations (e.g., “Parental leave duration in Engineering is 20% longer than company average—suggest updating policy to align with team needs”).
- Present analysis results in meetings (e.g., quarterly HR reviews) and tailor communication to non-technical audiences.
- Evaluate the effectiveness of existing LOA policies (e.g., “Is the new mental health leave policy reducing unplanned sick days?”) using data metrics and employee feedback.
- Provide data support for policy updates (e.g., adjusting paid leave limits, adding new leave types) to ensure alignment with labor laws (e.g., FMLA, EU Working Time Directive) and industry best practices.
- Collaborate with HRBP teams to communicate policy changes to employees and track adoption rates (e.g., how many employees use the new bereavement leave benefit).
- Partner with payroll teams to ensure LOA data integrates with payroll processes (e.g., accurate calculation of paid leave wages, deduction for unpaid leave).
- Work with department managers to address team-specific LOA issues (e.g., high leave turnover in Customer Service) and develop targeted solutions (e.g., cross-training staff for backup).
- Liaise with tech teams to enhance HRIS functionality for LOA data tracking (e.g., adding custom fields for leave reason codes, automating leave request workflows).
Minimum Qualifications
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- Bachelor’s degree in Data Science, Statistics, Human Resources Management, Business Analytics, or a related field. A master’s degree is a plus.
- Proficiency in data querying tools (SQL, HQL) to extract LOA data from HRIS/payroll systems; experience with data visualization tools (Tableau, Power BI, Qlik) and spreadsheet software (Advanced Excel: Pivot Tables, VLOOKUP,…
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