HR Analytics Role - Internet/Online

Key Responsibilities:

Data Collection and Management:

- Collect and aggregate HR data from multiple sources, including HRIS (Human Resources Information Systems), performance management systems, employee surveys, and other relevant data repositories.

Data Analysis and Reporting:

- Analyze HR data using statistical methods and data visualization techniques to uncover patterns, trends, and insights.

- Generate regular and ad-hoc reports on HR metrics, such as employee turnover, recruitment effectiveness, workforce diversity, and employee engagement.

- Present data findings and insights to HR leaders and stakeholders in a clear and concise manner, using data visualization tools and presentations.

Predictive Analytics and Modeling:

- Utilize advanced analytics techniques to develop predictive models and forecasts related to HR outcomes, such as attrition, performance, and talent acquisition.

- Identify key predictors and drivers of HR outcomes and develop strategies to proactively address potential issues and improve HR performance.

HR Strategy and Decision Support:

- Collaborate with HR leaders to understand their strategic goals and priorities and provide data-driven insights and recommendations to support their decision-making process.

- Conduct research and analysis on industry best practices and emerging trends in HR analytics to continuously improve HR strategies and practices.

- Assist in the development and monitoring of HR KPIs (Key Performance Indicators) and metrics to measure the effectiveness of HR initiatives.

Data Privacy and Compliance:

- Ensure compliance with data protection regulations and internal data privacy policies while handling sensitive HR data.

- Implement security measures to protect HR data confidentiality and integrity.

Qualifications:

- Bachelor's or Master's degree in Human Resources, Statistics, Data Science, Business Analytics, or a related field.

- Strong knowledge of HR processes and practices.

- Proficiency in data analysis and statistical techniques, including regression analysis, predictive modeling, and data visualization.

- Experience working with HRIS and other HR systems.

- Proficient in using data analytics tools, such as Excel, R, Python, or similar tools.

- Familiarity with HR metrics and analytics frameworks.

- Excellent communication skills, with the ability to present complex data findings to non-technical stakeholders.

- Strong problem-solving and critical-thinking abilities.

- Attention to detail and ability to work with large datasets.

- Experience with machine learning and advanced analytics techniques (preferred but not mandatory).