Project Manager, Data & AI

The Technical Project Manager combines strong project management discipline with a working understanding of modern data and AI technologies and development practices, enabling them to effectively manage technical dependencies, facilitate delivery decisions, identify risks, and drive projects from discovery and requirements through development, testing, implementation, and adoption. The role will manage multiple concurrent initiatives, establish and operate the team’s project intake and prioritization process, and help establish consistent delivery practices across the Data & AI team portfolio.

This position sits within the Data & Insights team and reports to the Director, Data & Analytics.

Your Contributions

Lead end-to-end delivery of data analytics and AI initiatives, including data engineering, integrations, analytics, reporting, governance, AI/ML use cases and data products from prototype through validated, launched solutions.
Own and continuously improve the team's project intake and prioritization process, ensuring incoming requests are scoped, triaged, and resourced against strategic priorities rather than handled ad hoc.
Develop and manage project plans, timelines, milestones, resources, dependencies, risks, and budgets across multiple concurrent initiatives.
Translate business and technical requirements into clear project scope, deliverables, workstreams, and actionable plans.
Partner with data engineers, analysts, business analysts, Product, IT, and other stakeholders to coordinate technical delivery and resolve dependencies.
Support new-business and existing-client opportunities involving data, analytics, or AI — partnering with Sales/Account teams on scoping, solution design, and pricing input for relevant RFPs and proactive business cases.
Manage Agile delivery activities, including backlog prioritization, sprint planning, stand-ups, retrospectives, and release planning.
Proactively identify and manage technical risks, issues, dependencies, and blockers, escalating and driving resolution as needed.
Coordinate testing, data validation, implementation, release readiness, and post-launch activities to ensure successful delivery.
Monitor project health and communicate progress, risks, decisions, and delivery forecasts to leadership and key stakeholders.
Manage project scope and change control, assessing impacts to timelines, resources, dependencies, and outcomes.
Ensure data governance, security, privacy, quality, and documentation requirements are incorporated into project delivery.
Manage external vendors and implementation partners, as applicable, to ensure delivery against agreed scope and timelines.
Track and report on delivery metrics tied to team goals, including reduction in ad hoc/BAU reporting work and adoption of launched AI/data solutions.
Support continuous improvement of Data & Insights delivery processes, tools, and standards while fostering accountability and collaboration across teams.

What We Are Looking For

Bachelor’s Degree preferred or equivalent practical / technical experience
Position requires 5-8 years of experience.
Strong understanding of data and analytics concepts, including data architecture, data modeling, data governance, data warehousing, and business intelligence.
Working knowledge of modern data technologies, including databases, ELT/ETL pipelines, APIs, integrations, SQL, and visualization platforms such as Power BI or Tableau.
Experience managing technical data and analytics projects through the full lifecycle, from requirements and design through testing, deployment, and adoption.
Strong knowledge of Agile/Scrum methodologies and proficiency with project delivery tools such as Jira, Asana, or Smartsheet.
Ability to understand technical architecture, dependencies, and risks and effectively facilitate discussions with engineers and technical specialists.
Strong project management, analytical, problem-solving, and organizational skills, with the ability to manage multiple concurrent initiatives.
Excellent communication and stakeholder management skills, with the ability to translate between technical and non-technical audiences.
PMP, CSM, PMI-ACP, or similar certification preferred; experience with cloud data platforms, AI/ML, or data products is a plus.
Strong communication skills and empathy for complex issues