Human Resources- Data Analyst

Description

Position Function: The HR Data Analyst is responsible for collecting, analyzing, and interpreting HR data to drive strategic decision-making and enhance HR processes. This involves developing dashboards and reports to track key metrics, collaborating with HR leadership to provide actionable insights, and ensuring data integrity and compliance. The analyst will leverage data analytics tools to support HR initiatives and communicate findings effectively to leadership. 

Education Requirements: Bachelor’s degree in computer science, data science, economics, experimental psychology, human resources, business, or related field preferred. Equivalent, relevant experience may be substituted. 

Experience/Skill Requirements:

• Two or more years of experience as an HR Analyst or in a similar role, with a strong understanding of HR processes.
• Experience using descriptive and/or inferential statistics to drive decision making.
• Experience with analytic tools, such as R, Python, SQL preferred.
• Experience with HRIS systems (e.g., Paylocity) preferred.
• Experience with data visualization tools (e.g. Microsoft Power BI, Tableau, Qliksense, SQL Reporting Services) preferred.
• Experience with cloud computing and automation preferred.
• Strong written and verbal communication skills.
• A commitment to continuous learning.
• Detail-oriented, with a commitment to data accuracy and confidentiality.

Working Conditions: Sitting long periods of time at computer.

Exposure to Confidential Information: This position involves exposure to confidential information about clients, personnel, and proprietary company practices. All confidential and sensitive information must be managed per company policy and applicable laws.

Key Expectations/Responsibilities:

• Maintain data quality by performing regular audits and implementing corrective actions.
• Analyze employee turnover, retention rates, and recruitment metrics to identify trends and provide insights.
• Create and distribute regular reports on HR metrics to management and relevant stakeholders.
• Design and maintain interactive dashboards using data visualization tools (e.g., Power BI, Qliksense, SQL Reporting Services) to track key HR performance indicators.
• Collaborate with HR team members to understand their data needs and provide insights that support talent acquisition, employee engagement, and workforce planning initiatives.
• Conduct ad hoc analyses to address specific HR challenges and inform strategic decisions.
• Foster collaboration between HR and other departments to promote a data-driven culture.
• Conduct regular audits of HR data to ensure data integrity and compliance with internal policies and external regulations.
• Document system configurations, processes, and training materials for end-users.
• Stay updated on the latest HR system (e.g. Paylocity) features, functionalities, and best practices to maximize the system's capabilities.
• Train and support users in accessing, interpreting and improving reporting tools.
• Troubleshoot problems or issues with reports.
• Champion efforts to improve data integrity, quality and normalization.
• Other duties as assigned.

Requirements

Education Requirements: Bachelor’s degree in computer science, data science, economics, experimental psychology, human resources, business, or related field preferred. Equivalent, relevant experience may be substituted. 

Experience/Skill Requirements:

• Two or more years of experience as an HR Analyst or in a similar role, with a strong understanding of HR processes.
• Experience using descriptive and/or inferential statistics to drive decision making.
• Experience with analytic tools, such as R, Python, SQL preferred.
• Experience with HRIS systems (e.g., Paylocity) preferred.
• Experience with data visualization tools (e.g. Microsoft Power BI, Tableau, Qliksense, SQL Reporting Services) preferred.
• Experience with cloud computing and automation preferred.
• Strong written and verbal communication skills.
• A commitment to continuous learning.
• Detail-oriented, with a commitment to data accuracy and confidentiality.