Product Owner

Job Title: Product Owner
Location: Hybrid role with 2 days in local Deloitte Office
Contract: 3+ Months

The Product Owner is accountable for one or more systems and AI-enabled capabilities, leading a cross-functional product team to deliver business value for both internal and external clients. This role partners closely with the Product Manager and broader firm leadership to shape, communicate, and deliver the product strategy and roadmap.
In an AI-focused team, the Product Owner translates business outcomes into measurable AI product requirements, prioritizes work across the end-to-end AI lifecycle (data, model development, deployment, and ongoing monitoring), and ensures solutions are designed and delivered responsibly. The Product Owner manages prioritization, requirements, timelines, and success criteria, harnessing multidisciplinary expertise to guide execution and maximize value delivery.

Key Responsibilities
Align product strategy with execution, maintaining the product roadmap and prioritizing the body of work for current and future delivery
Translate business problems into AI product epics and user stories with clear acceptance criteria, measurable outcomes, and defined human-in-the-loop decision points where needed
Partner with data science, data engineering, and software engineering to prioritize data require

Must Haves
Bachelor's degree in business administration, management information systems, computer science, or a related field
Proven experience in product ownership or management within financial services, client onboarding, or customer relationship systems
Broad and deep knowledge of financial services concepts, practices, and procedures, particularly in client onboarding or contact relationship systems
Experience delivering data-driven or AI-enabled products in partnership with engineering and data science teams (for example: recommendations, decisioning, document intelligence, workflow automation, or generative AI assistants)
Working knowledge of core AI/ML concepts (model training versus inference, features, drift, evaluation, and limitations) and ability to communicate trade-offs to non-technical stakeholders
Ability to define and manage measurable success criteria for AI features (for example: precision/recall, quality scoring, latency, adoption, and human-review rates)
Exceptional communication and interpersonal skills
Demonstrated analytical ability and attention to detail
Proven track record of leadership within matrixed teams, including task assignment, coaching, and mentoring
Teamwork/collaboration mindset with a demonstrated ability to work with and influence stakeholders across functions
Strong problem-solving skills and the ability to overcome ambiguity
Prior experience with Agile methodologies and a robust understanding of the full software development lifecycle

Good to Have
Advanced understanding of Product Management and Design Thinking principles and ability to expand these capabilities across teams
Experience with generative AI (LLMs), prompt and workflow design, and evaluation approaches for quality, safety, and reliability
Familiarity with MLOps practices and tooling (model deployment patterns, model registries, monitoring/alerting, and incident response)
Experience partnering with risk, legal/compliance, privacy, and information security to meet model governance and regulatory expectations (for example: documentation, auditability, and controls)
Experience in digital product ownership with exposure to high-performing teams and ongoing professional development of team members
History of working on multi-disciplinary and cross-divisional product teams
Experience guiding the management of resource needs, dependencies, and stakeholder solution requirements
Demonstrated ability to advise and align with adjacent product teams to ensure consistent and cohesive delivery across products
Background in building business cases and measuring delivery against defined success criteria