Portfolio Manager - Data, AI & Analytics

Req ID: 384501

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Portfolio Manager - Data, AI & Analytics to join our team in Hyderabad, Telangana (IN-TG), India (IN).

Job Description: Portfolio Manager – Data, AI & Analytics (Life Sciences) Job Title - Portfolio Manager – Data, AI & Analytics Experience: 12+ Years

Location: Remote/Hybrid (Travel as Required)

Project Overview We are seeking an experienced Portfolio Manager to lead a portfolio of strategic Data, Artificial Intelligence (AI), Machine Learning (ML), and Analytics initiatives within a global Life Sciences organization. This role is responsible for driving enterprise-wide data and AI transformation programs that enable advanced analytics, intelligent automation, predictive insights, and AI-powered decision-making across Research & Development (R&D), Manufacturing, Quality, Supply Chain, Commercial, and Corporate functions.

The ideal candidate will possess extensive experience managing enterprise Data & AI portfolios, delivering large-scale analytics platforms, AI/ML solutions, and cloud-based data ecosystems in highly regulated Life Sciences environments. This role requires close collaboration with business leaders, Data Science, IT, Digital, Enterprise Architecture, Cybersecurity, and external implementation partners to deliver scalable, secure, and compliant digital solutions.

Key Responsibilities Portfolio Management

• Lead and govern a portfolio of enterprise Data, AI, and Analytics initiatives across multiple business units and global regions.
• Define portfolio strategy, digital roadmap, investment priorities, budgets, and resource allocation aligned with business objectives.
• Establish portfolio governance, executive dashboards, KPIs, and value realization metrics.
• Monitor portfolio health, financial performance, risks, dependencies, and delivery milestones.
• Drive prioritization of AI and analytics initiatives based on business value and strategic alignment.

Program & Project Leadership

• Manage multiple concurrent enterprise programs involving data platforms, AI solutions, analytics modernization, and intelligent automation.
• Oversee end-to-end delivery including strategy, architecture, implementation, testing, deployment, adoption, and operational transition.
• Coordinate cross-functional delivery teams, business stakeholders, vendors, and implementation partners.
• Manage program risks, dependencies, budgets, schedules, and executive communications.

Data, AI & Analytics Transformation

• Lead enterprise initiatives involving:

• Data Modernization
• Enterprise Data Platforms
• Data Lakes and Lakehouses
• Data Warehousing
• Advanced Analytics
• Business Intelligence
• Artificial Intelligence (AI)
• Machine Learning (ML)
• Generative AI
• Intelligent Automation
• Predictive Analytics

• Self-Service Analytics

• Drive enterprise AI adoption, governance, and responsible AI practices.
• Support modernization of enterprise reporting, dashboards, and analytics capabilities.
• Promote data-driven decision-making and enterprise-wide analytics adoption.

Business & Stakeholder Management

• Partner with R&D, Manufacturing, Quality, Supply Chain, Commercial, Finance, Regulatory Affairs, and IT leadership.
• Collaborate with Data Scientists, AI Engineers, Data Engineers, Architects, and Product Owners to prioritize and deliver strategic initiatives.
• Facilitate executive steering committee meetings and portfolio governance reviews.
• Drive organizational change management and user adoption for Data & AI solutions.

Data Governance & Compliance

• Ensure enterprise data platforms and AI solutions comply with Life Sciences regulatory and governance requirements, including:

• GxP
• FDA 21 CFR Part 11
• EU Annex 11
• ALCOA+ Data Integrity Principles
• Computer Software Assurance (CSA)
• Data Privacy and Security standards

• Responsible AI and AI Governance frameworks

• Establish governance for enterprise data quality, metadata management, master data, and AI lifecycle management.

Financial & Vendor Management

• Manage portfolio budgets, forecasts, resource planning, and financial reporting.
• Oversee relationships with cloud providers, software vendors, consulting pa…