HR Data Analyst

Key Responsibilities:

• Data Collection and Analysis: Collect, clean, and analyze HR data from various sources, including HRIS (Human Resources Information Systems), performance management systems, employee surveys, and other relevant databases.

• Metrics Development: Develop and maintain key HR metrics and KPIs (Key Performance Indicators) to track and measure workforce trends, employee engagement, retention, turnover, diversity, performance, and other relevant HR metrics.

• Trend Identification: Identify patterns, trends, and correlations within HR data to provide insights into employee behavior, performance drivers, and organizational dynamics.

• Predictive Analytics: Utilize statistical modeling and predictive analytics techniques to forecast future workforce trends, attrition rates, talent gaps, and other critical HR metrics.

• Dashboard Development: Design and create dashboards and data visualizations to present HR metrics and insights in a clear, concise, and actionable format for HR leadership and other stakeholders.

• Ad Hoc Analysis: Conduct ad hoc analysis and deep dives into specific HR issues or initiatives, providing actionable recommendations to HR leadership based on data-driven insights.

• Data Integrity and Compliance: Ensure the accuracy, integrity, and security of HR data, adhering to relevant data privacy regulations and best practices in data management.

• Collaboration: Collaborate cross-functionally with HR business partners, talent acquisition teams, compensation and benefits specialists, and other stakeholders to leverage HR data for strategic decision-making and process improvement initiatives.

Qualifications:

• Bachelor's degree in HR, Business Administration, Statistics, Data Science, or a related field (Master's degree preferred).
• 2 years of experience working with HRIS - SAP SuccessFactors.
• 5 years of experience in HR analytics, data analysis, or a related role.
• Proficiency in data analysis tools and programming languages such as Excel, SQL, Python, R, or similar tools.
• Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights.
• Excellent communication and presentation skills, with the ability to convey technical information to non-technical stakeholders.
• Detail-oriented with a commitment to data accuracy and quality.