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Project Manager, Data and AI
HybridNot specifiedProject Management
Lead complex technology projects from initiation through production and coordinate a portfolio of projects in a large organization. Work with product, development, data and AI, infrastructure, security, business, and external vendor teams. The work arrangement is hybrid.
Responsibilities
- Lead complex technology projects in data, AI, and information systems from initiation and requirements definition through implementation and production launch.
- Build project plans and manage milestones, schedules, resources, budgets, dependencies, and risks.
- Manage key projects directly and coordinate and monitor the unit's project portfolio.
- Coordinate with product managers, development and data and AI teams, infrastructure, cloud, information security, systems, business stakeholders, and external vendors.
- Lead integration and implementation processes and oversee external vendors and their deliverables.
- Deliver projects using Agile and hybrid or Waterfall approaches as appropriate.
- Establish structured working processes, define performance indicators, track status, and document lessons learned.
Requirements
- At least four years of end-to-end project management experience with complex IT, software, or information systems projects.
- Experience managing multiple projects or workstreams in a technology environment with many stakeholders.
- Experience developing work plans and managing schedules, resources, risks, and dependencies.
- Experience working with development, infrastructure, information security, systems, and business teams.
- Experience working with Agile methodology.
- Good technical understanding of systems architecture, interfaces, infrastructure, and development environments.
- Ability to coordinate professional teams across organizational lines without direct authority.
- Academic degree in computer science, computer engineering, industrial engineering and management with an information systems focus, information systems management, or another academic field combined with information systems coursework; alternatively, a computer or technology practical engineering qualification.
Nice to have
- Experience with AI, generative AI, machine learning, data engineering, or analytics projects.
- Experience leading a proof of concept or pilot through production.
- Experience with cloud projects, particularly AWS.
- Experience managing external technology vendors or development firms.
- Familiarity with Jira or Azure DevOps.
- Previous software development, systems analysis, or other technology experience.
- Knowledge of information security, privacy, or data governance in data and AI projects.