Lead - People AI

Lead, People AI

Company: Piramal Finance

Experience: 7–11 years

Location: Bengaluru

About the Role:

We are looking for a Lead, People AI to drive data-led decision-making across workforce management, employee performance, productivity, and organisational effectiveness. The ideal candidate will combine strong Data Science, AI/ML, and People Analytics expertise with proven people management and leadership skills.

The role will focus on building AI-driven solutions and analytical models across employee attrition, incentive effectiveness, Performance Management Systems (PMS), and workforce productivity. The candidate will lead and mentor a team of data scientists and analysts, collaborate with senior stakeholders, and translate complex workforce data into actionable business insights.

Key Responsibilities:

1. People Analytics and Workforce Intelligence

• Lead People Analytics, Workforce Analytics, and People AI initiatives to support strategic workforce planning and organisational decision-making.
• Analyse employee lifecycle data to identify trends and opportunities to improve workforce effectiveness, productivity, and retention.
• Develop analytical frameworks to measure employee performance, engagement, productivity, and organisational health.
• Translate complex workforce data into actionable insights and recommendations for senior leadership.

2. Attrition and Retention Analytics

• Develop statistical and predictive models to identify attrition drivers, retention risks, and employee turnover patterns.
• Analyse factors influencing attrition, including compensation, performance, tenure, career progression, and organisational dynamics.
• Build data-driven interventions to improve employee retention and support proactive workforce planning.
• Measure the effectiveness of retention strategies through analytics and outcome tracking.

3. Incentive and Performance Analytics

• Analyse employee incentive structures, variable pay, and reward programmes to evaluate their effectiveness and business impact.
• Develop analytical models to assess the relationship between incentives, employee performance, productivity, and business outcomes.
• Drive data-led insights for Performance Management Systems (PMS), including performance distribution, rating trends, goal achievement, and performance differentiation.
• Identify opportunities to improve incentive effectiveness, performance measurement, and reward frameworks.

4. AI/ML and Advanced Analytics

• Apply statistical modelling, machine learning, and AI techniques to solve complex people and workforce-related problems.
• Develop predictive and prescriptive analytics solutions for attrition, productivity, employee performance, and workforce planning.
• Identify opportunities to leverage AI and automation to improve HR processes and decision-making.
• Build scalable analytical solutions, dashboards, and decision-support tools that enable business teams to act on insights.

5. People Management and Team Leadership

• Lead, manage, and mentor a team of data scientists and analysts, providing direction, coaching, and regular feedback.
• Set clear goals, define priorities, and ensure timely delivery of high-quality analytical projects.
• Build a collaborative, high-performance team culture that encourages ownership, innovation, continuous learning, and accountability.
• Support team members in developing their technical, analytical, and problem-solving capabilities.
• Review analytical approaches, model outputs, and project deliverables to ensure quality, accuracy, and business relevance.
• Manage resource allocation, project planning, and competing priorities while ensuring alignment with business objectives.
• Identify opportunities to strengthen team capabilities in AI, machine learning, advanced analytics, and People Analytics.

6. Stakeholder Management and Business Partnership

• Partner with HR, business leaders, Finance, and technology teams to identify business challenges and translate them into analytical solutions.
• Present insights, recommendations, and business impact to senior stakeholders in a clear and actionable manner.
• Influence business decisions through data-backed recommendations and measurable outcomes.
• Establish best practices for data quality, model validation, analytics governance, and the responsible use of employee data.

What We’re Looking For:

• 7–11 years of relevant experience in Data Science, People AI, People Analytics, Workforce Analytics, or HR Analytics.
• Strong hands-on experience in one or more of the following areas: employee attrition, incentive analytics, PMS/performance analytics, workforce productivity, or people analytics.
• Proven people management experience, including leading teams, mentoring professionals, setting goals, and managing performance and delivery.
• Experience applying statistical modelling, machine learning, and predictive analytics to real-world business problems.
• Strong proficiency in Python and SQL, with experience using data visualisation tools such as Power BI or Tableau.
• Ability to work with large and complex datasets, identify meaningful patterns, and translate findings into business recommendations.
• Strong stakeholder management, communication, decision-making, and problem-solving skills.
• Ability to balance technical depth with team leadership and business priorities.

Good to Have:

• Experience building AI-driven solutions for HR or workforce management.
• Exposure to compensation analytics, incentive design, performance management, employee engagement, and workforce planning.
• Experience working with HRIS platforms and integrating data from multiple enterprise systems.
• Experience in BFSI, fintech, or other large, data-driven organisations.

What Success Looks Like:

• Improved understanding and prediction of employee attrition.
• Better visibility into workforce productivity and performance drivers.
• Data-backed improvements in incentive effectiveness and PMS outcomes.
• Successful adoption of AI-driven solutions across people and workforce-related decisions.
• A high-performing analytics team with strong technical capabilities, ownership, and accountability.
• Measurable business impact through effective team leadership, stakeholder collaboration, and data-driven decision-making.