Lead - People AI

Piramal Finance; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Piramal Finance in Bengaluru, India, seeks a Lead, People AI to drive data-led decision-making across workforce management, performance, productivity and organisational effectiveness. You will lead a team of data scientists and analysts, partnering with senior stakeholders to translate workforce data into actionable insights.

The role focuses on attrition and retention analytics, incentive and PMS analytics, and the development of AI-driven solutions, dashboards and decision-support tools to

Qualifications

• 7–11 years of experience in Data Science, People Analytics, or HR analytics.

Responsibilities

• Lead People Analytics initiatives to support strategic workforce planning.
• Develop models to identify attrition drivers and retention risks.
• Build AI-driven analytics solutions for PMS and productivity.
• Lead and mentor a team of data scientists and analysts.
• Partner with HR and leaders to translate data into business insights.

Skills

People analytics

Leadership

Team management

Decision making

Tools

Python

SQL

Power BI

Tableau

Job description

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.