HR Analytics

Role overview

Responsibilities

• check_circle Build and maintain HR dashboards and reports using Power BI, Tableau, or similar visualization tools.
• check_circle Use Python and SQL to clean, analyze, and automate HR data reporting.
• check_circle Develop predictive analytics models to identify trends such as attrition risk, hiring demand, and workforce planning.
• check_circle Support AI-driven HR initiatives by leveraging Generative AI and automation tools to improve reporting and employee insights.
• check_circle Partner with HR, Talent Acquisition, Finance, and HR Operations teams to understand business requirements and deliver data-driven solutions.
• check_circle Ensure data quality, accuracy, and consistency across HR systems and reports.
• check_circle Prepare recurring and ad-hoc MIS reports for leadership reviews.
• check_circle Identify opportunities to automate manual reporting processes and improve operational efficiency.
• check_circle Present analytical findings through clear visualizations and business-friendly insights.

Basic qualifications

• Bachelor's or Master's degree in Engineering, Computer Science, Statistics, Mathematics, Business Analytics, Human Resources, or a related field.
• 2–6 years of experience in HR Analytics, People Analytics, Business Analytics, or Data Analytics.
• Strong hands-on experience with Python (Pandas, NumPy) for data analysis and automation.
• Good knowledge of SQL for querying and managing datasets.
• Experience with Power BI, Tableau, or other BI visualization tools.
• Understanding of HR metrics such as hiring, attrition, diversity, headcount, and workforce planning.
• Basic knowledge of AI/ML concepts or experience using AI tools for analytics and automation.
• Strong analytical, problem-solving, and communication skills.
• Proficiency in Microsoft Excel.

Preferred qualifications

• Exposure to HRIS platforms
• Familiarity with Generative AI tools (ChatGPT, Microsoft Copilot, Gemini, Claud) and their application in HR analytics.
• Knowledge of statistical analysis and data visualization best practices.
• Experience working in a fast-paced technology or fintech environment.