HR Analytics

About the role

Paytm is seeking an analyst to drive our People Analytics strategy by converting raw human resources data into clear business intelligence. You will collaborate with internal stakeholders to automate reporting workflows and apply predictive modeling to improve workforce decision-making.

Key facts

What you'll do

• Design and manage HR dashboards using visualization software.
• Clean and process datasets using SQL and Python to streamline reporting.
• Build predictive models to forecast hiring needs, attrition patterns, and workforce planning requirements.
• Integrate Generative AI and automation tools to enhance employee insights and reporting efficiency.
• Coordinate with business leaders and HR partners to fulfill data requests and define metrics.
• Maintain high standards of data integrity across all HR systems.
• Generate and present MIS reports for management reviews.
• Replace manual reporting tasks with automated solutions.

Requirements

• Bachelor or Master degree in Engineering, Computer Science, Statistics, Mathematics, Business Analytics, or Human Resources.
• 2 to 6 years of professional experience in People, HR, or Business Analytics.
• Proficiency in Python libraries such as Pandas and NumPy for data manipulation.
• Competency in SQL for database querying.
• Hands-on experience with Power BI, Tableau, or similar BI tools.
• Advanced Microsoft Excel skills.
• Familiarity with HR-specific metrics including headcount, diversity, hiring, and attrition.
• Foundational knowledge of AI and machine learning concepts.

Nice to have

• Experience working with HRIS platforms.
• Practical application of Generative AI tools like ChatGPT, Microsoft Copilot, Gemini, or Claude within an HR context.
• Background in a fintech or high-growth technology company.
• Expertise in statistical analysis and visual design principles.

Skills & tools

• Data Analysis and Visualization
• Python, SQL, VBA, Power BI, Tableau
• HR Metrics and Workforce Planning
• AI and Automation
• Stakeholder Management
• Statistical Modeling

Practical notes

• Candidates should be prepared to demonstrate their ability to translate complex data into actionable business narratives for leadership.