Associate Director - Data Science

Principal Financial Group; Pune District; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Principal Financial Group seeks a senior leader to define and execute an enterprise AI and data science vision. You will manage investments, partnerships, and cross-department initiatives to deliver a practical AI portfolio with measurable impact on revenue, costs, and customer outcomes.

The role requires 20+ years of leadership across AI, data, and digital transformation, with a track record of building scalable enterprise AI strategies and governance frameworks.

Qualifications

• Degree in engineering, computer science, data science, mathematics, or a related field.
• 20+ years of progressive leadership experience across Data, Analytics, Artificial Intelligence, and Digital Transformation.
• Proven history in designing enterprise AI strategies and multi-year roadmaps with measurable outcomes.
• Lead large, cross-functional teams including Data Science, AI Engineering, Analytics, MLOps, Product Management, and Program Delivery.
• Experience partnering with C-suite executives to align strategy, investments, and governance.

Responsibilities

• Define the enterprise AI vision and multi-year agenda, overseeing funding, sequencing, and benefits realization.
• Drive business value realization, tracking ROI, adoption, efficiency, risk, and impact.
• Lead enterprise AI platforms and solutions, including RAG, AI agents, and document intelligence.
• Establish responsible AI governance, policies, data privacy, security, and compliance.
• Oversee cross-functional delivery across Data Science, Analytics Engineering, AI Engineering, and MLOps.
• Build and nurture high-performing teams and strategic partnerships to accelerate outcomes.

Skills

Executive leadership

Strategic planning

Cross-functional

AI governance

Enterprise AI

Portfolio management

Stakeholder management

Risk management

Education

Engineering degree

Data science degree

Tools

MLOps

LLMOps

NLP

AI governance tools

Job description

• The leader of AI and Data Science at the enterprise level defines the organization’s overarching AI vision, manages investments, and leads cross-departmental initiatives to expand responsible AI. This role partners with executive, business, and technology leaders to transform strategic priorities into a practical AI portfolio, enterprise capabilities, and quantifiable results across revenue growth, cost savings, efficiency, customer satisfaction, and risk management.
• Enterprise AI strategy and investment governance: Set the enterprise AI vision, multi-year agenda, and operating system. Formulate arguments, order high-value use cases, and supervise funding, sequencing, dependencies, delivery risk, and benefits realization.
• Business value realization and executive advisory: Establish measurable outcomes and track adoption, efficiency, reliability, risk, return on investment, and business impact. Translate AI opportunities, constraints, and choices into executive-ready recommendations and implementation roadmaps.
• Enterprise AI platforms and solutions: Support scalable features such as retrieval-augmented generation, AI agents, intelligent automation, document intelligence, MLOps/LLMOps, and model and agent observability.
• Responsible AI and lifecycle governance: Establish policies, standards, and controls covering data privacy, security, model risk, bias minimization, regulatory alignment, monitoring, and ethical AI implementation.
• Cross-functional delivery, adoption, and change: Lead multidisciplinary implementation efforts across Data Science, Analytics Engineering, AI Engineering, MLOps/LLMOps, and Agent Enablement. Encourage uptake by supporting organizational transformation and integrating solutions into business workflows.
• Assemble, guide, and sustain high-performing teams. Advance enterprise AI capabilities. Handle strategic technology partnerships to drive outcomes faster while controlling costs and vendor risk.

What You’ll Do

• The leader of AI and Data Science at the enterprise level defines the organization’s overarching AI vision, manages investments, and leads cross-departmental initiatives to expand responsible AI. This role partners with executive, business, and technology leaders to transform strategic priorities into a practical AI portfolio, enterprise capabilities, and quantifiable results across revenue growth, cost savings, efficiency, customer satisfaction, and risk management.
• Enterprise AI strategy and investment governance: Set the enterprise AI vision, multi-year agenda, and operating system. Formulate arguments, order high-value use cases, and supervise funding, sequencing, dependencies, delivery risk, and benefits realization.
• Business value realization and executive advisory: Establish measurable outcomes and track adoption, efficiency, reliability, risk, return on investment, and business impact. Translate AI opportunities, constraints, and choices into executive-ready recommendations and implementation roadmaps.
• Enterprise AI platforms and solutions: Support scalable features such as retrieval-augmented generation, AI agents, intelligent automation, document intelligence, MLOps/LLMOps, and model and agent observability.
• Responsible AI and lifecycle governance: Establish policies, standards, and controls covering data privacy, security, model risk, bias minimization, regulatory alignment, monitoring, and ethical AI implementation.
• Cross-functional delivery, adoption, and change: Lead multidisciplinary implementation efforts across Data Science, Analytics Engineering, AI Engineering, MLOps/LLMOps, and Agent Enablement. Encourage uptake by supporting organizational transformation and integrating solutions into business workflows.
• Assemble, guide, and sustain high-performing teams. Advance enterprise AI capabilities. Handle strategic technology partnerships to drive outcomes faster while controlling costs and vendor risk.

Who You Are

• Degree in engineering, computer science, data science, mathematics, or a related field, or equivalent experience.
• 20+ years of progressive leadership experience across Data, Analytics, Artificial Intelligence, and Digital Transformation, with significant accountability for enterprise-scale portfolios, strategic investments, and groundbreaking business outcomes.
• Proven history in designing and progressing enterprise AI, Data, and Analytics strategies, transforming vision into multi-year plans, scalable operating frameworks, technological capacities, and measurable business results.
• Proven ability to lead large, cross-functional teams spanning Data Science, AI Engineering, Analytics Engineering, Data Platform Engineering, MLOps/LLMOps, Product Management, and Program Delivery functions.
• Extensive experience partnering with C-suite executives, senior business leaders, and technology collaborators to build strategy, prioritize investments, manage organizational change, and accelerate business outcomes.
• Strong expertise in establishing and operationalizing AI governance, model lifecycle management, responsible AI frameworks, risk controls, compliance standards, security guardrails, and enterprise monitoring practices.
• Experience leading and providing production-scale solutions demonstrating Machine Learning, Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), Intelligent Automation, Knowledge Systems, and Document Intelligence.
• Demonstrated success leading large-scale enterprise transformation initiatives, including operating model modernization, capability development, process optimization, and technology-based business innovation.
• Experience assembling and advancing high-performing teams while supporting a culture of innovation, accountability, collaboration, and continuous learning.

Global Leadership & Collaborator Management

• Extensive experience operating within complex Global Capability Center (GCC) environments, with a deep understanding of how GCCs enable enterprise growth, innovation, talent development, and operational excellence.
• Established track record of guiding strategy, promoting alignment, and producing results within globally distributed, complex organizations covering various business units, functions, geographies, and cultures.
• Proven history of building positive connections with executive leadership, business sponsors, technology leaders, external partners, and strategic collaborators, acting as a trusted advisor on enterprise AI, data, and transformation projects.
• Demonstrated success navigating organizational complexity, prioritizing various tasks, and aligning diverse collaborator interests to achieve enterprise objectives.
• Ability to exercise enterprise influence beyond direct span of control, establish accountability, and lead through collaboration, negotiation, and strategic relationship management.
• Demonstrated success in guiding organizational transformation and acceptance, fostering agreement among senior leadership groups, and managing company-wide projects that produce balanced business outcomes.
• Strong executive presence, communication, and collaborator engagement talents, coupled with the skill to transform complex technology strategies into engaging business narratives for senior executives and board-level audiences.

Differentiating Capabilities

• Deep understanding of modern AI and data technologies, including Generative AI, Agentic AI, Large Language Models (LLMs), RAG, Vector Search, Embeddings, Prompt Engineering, Machine Learning, NLP, Document Intelligence, MLOps/LLMOps, and Cloud AI Platforms.
• Strategic and goal-focused leader capable of balancing innovation, value realization, scalability, security, governance, adherence to regulations, and risk management.
• Demonstrated ability to build enterprise priorities, influence executive decision-making, and drive outcomes across organizational boundaries.
• Strong leadership presence with the ability to communicate complex technical concepts, risks, trade-offs, and investment decisions in a clear and engaging way.
• Demonstrated capability in attracting, developing, mentoring, and retaining top talent while fostering leadership depth and long-term organizational strength.
• Skilled at leading through ambiguity, managing competing priorities, and delivering results in fast-paced, evolving business environments.
• Acknowledged for promoting a culture of innovation, operational excellence, customer focus, and continuous improvement while maintaining a strong dedication to responsible and ethical AI adoption.