Job Summary

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

Role Overview

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 (RD), 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.

Business Stakeholder Management
- Partner with RD, 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 partners, and implementation teams.




- Manage contracts, Statements of Work (SOWs), vendor performance, and service-level commitments.
- Track portfolio benefits, business outcomes, operational improvements, and return on investment (ROI).

Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, Business Analytics, or a related discipline.
- Master's degree is preferred.
- 12+ years of overall IT and Digital Transformation experience.
- 5+ years managing enterprise portfolios or large-scale programs focused on Data, AI, and Analytics.
- 5+ years of proven experience leading enterprise data modernization and AI transformation initiatives.
- 5+ years of strong experience within the Pharmaceutical, Biotechnology, Medical Devices, or broader Life Sciences industry.
- 5+ years of demonstrated experience managing executive stakeholders, global delivery teams, vendors, and implementation partners.

Required Technical Functional Expertise
- Portfolio Program Management
- Enterprise Data Strategy
- Data AI Transformation
- Data Engineering
- Data Governance
- Data Quality
- Cloud Data Platforms
- Executive Stakeholder Management
- Vendor Financial Management
- Risk Governance

Preferred Technical Experience Experience with one or more of the following technologies and platforms:
- Azure Data Platform
- Microsoft Fabric
- Azure AI Services
- Azure OpenAI
- AWS Data AI Services
- Databricks
- Snowflake
- Azure Synapse Analytics
- Azure Data Factory
- Microsoft Power BI
- Tableau
- SQL
- Python
- Apache Spark / PySpark
- Azure AI Search
- LangChain
- Vector Databases
- Microsoft Purview
- Informatica MDM
- Collibra
- MLflow
- Langfuse

Preferred Certifications
- PMP or PgMP
- PMI Portfolio Management Professional (PfMP)
- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Certified: Azure Solutions Architect Expert
- Databricks Certified Professional
- AWS Certified Solutions Architect
- SAFe Agilist or Protected Program Consultant (SPC)
- ITIL Foundation
- Lean Six Sigma Green Belt or Black Belt

Key Skills
- Portfolio Management
- Program Management
- Data Strategy
- Data Platforms
- Analytics

📌 Portfolio Manager - Data, AI & Analytics (Hyderabad)
🏢 NTT DATA Business Solutions
📍 Hyderabad