UST
Website:
ust.com
Job details:
Role Description
Job Title
Portfolio Lead - Data & Artificial Intelligence
Role Summary
We are seeking a
Portfolio Lead - Data & Artificial Intelligence to define, govern, and drive the enterprise-wide Data & AI portfolio, ensuring alignment to strategic priorities and measurable business value.
This role operates above individual programs, owning
portfolio strategy, prioritization, investment decisions, and value realization across Data platforms, analytics, and AI/ML initiatives. The Portfolio Lead ensures that initiatives are not only delivered effectively but are
cohesively aligned, sequenced, and optimized for enterprise impact.
You will act as the
single point of accountability for Data & AI portfolio outcomes, partnering with executive leadership to translate business strategy into a balanced, scalable, and high-impact portfolio roadmap.
This is a
strategic and execution-governance role, requiring strong commercial acumen, deep understanding of data and AI ecosystems, and the ability to drive decisions across competing priorities.
Key Responsibilities
Portfolio Strategy & Governance
- Own the end-to-end Data & AI portfolio, including strategy, planning, prioritization, and governance
- Define and maintain a multi-year portfolio roadmap aligned to enterprise objectives
- Establish portfolio governance frameworks (intake, prioritization, funding, and review cycles)
- Lead executive-level portfolio reviews, ensuring transparency on progress, risks, and value
Demand Management & Prioritization
- Drive structured demand intake and evaluation across business units
- Prioritize initiatives based on business value, feasibility, risk, and strategic alignment
- Balance investments across:
- Data platform foundations
- Analytics & reporting
- AI/ML use cases
- Ensure optimal allocation of resources across competing initiatives
Value Realization & Financial Oversight
- Own portfolio-level financial planning, budgeting, and investment tracking
- Define and track ROI, KPIs, and value realization metrics across initiatives
- Ensure initiatives deliver measurable business outcomes, not just technical outputs
- Continuously optimize portfolio mix based on performance and evolving priorities
Program Oversight & Execution Assurance
- Provide oversight across all Data & AI programs, ensuring alignment to portfolio goals
- Establish consistent delivery standards, governance, and reporting frameworks
- Intervene and course-correct programs at risk (scope, timeline, value)
- Ensure seamless integration across data, analytics, and AI initiatives
Data & AI Strategy Alignment
- Ensure strong alignment between:
- Data platform maturity
- AI/ML roadmap and ambitions
- Drive enterprise adoption of scalable data and AI patterns
- Prevent fragmentation by eliminating siloed or redundant initiatives
- Promote transition from POCs to enterprise-scale deployments
Stakeholder & Executive Engagement
- Partner with senior executives to shape and evolve Data & AI strategy
- Lead executive steering forums and decision-making bodies
- Communicate portfolio performance, trade-offs, and strategic recommendations
- Influence cross-functional leaders across business and technology
Risk, Compliance & Governance
- Own portfolio-level risk management (RAID) and mitigation strategies
- Ensure compliance with data governance, privacy, and regulatory standards
- Monitor risks related to:
- Data quality and integrity
- AI model bias and ethics
- Operational and deployment stability
Operating Model & Capability Building
- Define and evolve the Data & AI operating model
- Establish best practices across DataOps, MLOps, and program governance
- Drive maturity in tools, frameworks, and ways of working
- Enable collaboration across data engineering, analytics, and data science teams
Required Qualifications
- 12+ years of experience in Data, AI, or technology portfolio/program leadership
- Proven experience managing multi-program or portfolio-level initiatives
- Strong understanding of:
- Enterprise data platforms (data lakes, warehouses, lakehouse)
- Data governance and lifecycle management
- AI/ML lifecycle and production deployment
- Demonstrated ability to drive investment decisions and prioritization
- Experience working with executive stakeholders and steering committees
- Strong financial and commercial acumen (budgeting, ROI tracking)
Preferred Qualifications
- Experience in regulated industries (life sciences, healthcare, financial services)
- Familiarity with modern data ecosystems (Snowflake, Databricks, AWS, Azure, GCP)
- Exposure to DataOps, MLOps, and platform-based delivery models
- Certifications (PgMP, PMP, Agile, cloud certifications)
- Experience managing global and distributed portfolios
Critical Skills / Competencies
- Portfolio Ownership & Strategic Thinking - Drives enterprise-level outcomes
- Investment & Value Orientation - Focuses on ROI and measurable impact
- Data & AI Fluency - Understands the full ecosystem and dependencies
- Executive Influence - Drives alignment and decision-making at senior levels
- Prioritization & Trade-off Management - Balances competing demands effectively
- Governance & Risk Management - Ensures control without slowing execution
- Systems Thinking - Connects initiatives into a cohesive ecosystem
Experience Profile
The ideal candidate will demonstrate:
- Ownership of enterprise Data & AI portfolios, not just individual programs
- Experience managing multiple concurrent initiatives with interdependencies
- Strong track record of portfolio prioritization and investment optimization
- Ability to connect data foundations to AI-driven business outcomes
- Experience influencing C-level stakeholders and strategic decisions
- Delivery of measurable business value at scale
Skills
artificial intelligence,data,mlops,dataops,analytics,data platforms,ai/ml,
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