Responsibilities

About the Team: 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). Key Responsibilities: 1. LOA Data Collection & Governance - Gather end-to-end LOA data from multiple sources (HRIS systems like Workday/SAP SuccessFactors, payroll platforms, leave request portals, and manual records). - Ensure data accuracy per payroll cycle; monitor data quality over time and troubleshoot data discrepancies (e.g., mismatches between leave requests and payroll deductions) with cross-functional teams. - Ensure data completeness, consistency through regular data cleaning (e.g., resolving duplicate entries, standardizing leave types, validating date formats) and establishing data governance rules (e.g., defining LOA data metrics, updating data dictionaries). 2. LOA Data Analysis & Trend Identification - 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, unusually long unpaid leave) 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. - 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). 3. Reporting & Visualization - 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. 4. Policy Optimization & Compliance Support - 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). 5. Cross-Functional Collaboration - 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).

Qualifications

Minimum Qualifications: - 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: PivotTables, VLOOKUP, macros). - Basic knowledge of statistical analysis (e.g., trend analysis, correlation, forecasting) and data cleaning techniques. - Familiarity with HRIS platforms (Workday, ADP) is highly preferred. - Understanding of leave-of-absence types (sick, parental, medical, unpaid, statutory leave) and relevant labor laws (e.g., FMLA, region statutory leave regulations). - Knowledge of HR operations (payroll, workforce planning, employee relations) to contextualize LOA data insights. - Strong analytical thinking: Ability to translate business problems into data questions and derive actionable insights. Preferred Qualifications: - 3-5 years of experience in HR analytics, workforce analytics, or data analysis (preferably with a focus on leave management, payroll, or employee relations). - Communication: Excellent communication and written skills to present complex data to non-technical stakeholders. - Attention to detail: Ensures data accuracy and avoids errors in analysis/reporting. - Collaboration: Ability to work cross-functionally with HR, payroll, IT, and department teams. - Time management: Prioritizes multiple tasks (e.g., urgent anomaly investigations, regular report deadlines) in a fast-paced environment. - Certification in data analytics (e.g., Google Data Analytics Professional Certificate, Tableau Desktop Specialist) or HR (e.g., SHRM-CP, PHR). - Experience working in a global organization (familiarity with US leave policies and multi-country data standards).

Job Information