Associate Director - Data Science

at Principal

Pune, India, hybrid, executive, full time, 20+ years

seen 4d ago

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Generative AI
LLMs
Document Intelligence
LLMOps
Natural Language Processing
Retrieval-Augmented Generation
Machine Learning
Vector Search
Agentic AI
Intelligent Automation
Embeddings
Prompt Engineering
NLP
MLOps
Cloud AI Platforms
RAG
Large Language Models

About the role

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* 53392 * Data Science & Analytics * Regular Full-Time * Pune, India * H880 - PGS Global Center Pune * In-Office few days a week (a minimum of 3 days in office) and Work from Home * PSINPADSM PG22-PADSM PG22

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What you would 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.

Read from careers.principal.com, last seen 4d ago.

What they are looking for

- 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.