Product Owner (OmniAnalyst)

Sedgwick•Memphis, TN

1d•Hybrid

About The Position

The Product Owner plays a key role in building Sedgwick's next-generation, AI-forward data analytics platform. This tool is designed to provide trusted, actionable insights to users faster than ever before. The role involves translating business needs into actionable requirements, managing the product backlog, and ensuring delivery drives meaningful business outcomes. The Product Owner will also validate delivered functionality, track adoption, and shape how AI capabilities like natural-language querying, automated insight generation, and intelligent recommendations are implemented for users across the enterprise. This role may also execute delegated Product Manager activities when capacity or capability constraints exist.

Requirements

Bachelor's degree in Business Administration, Information Systems, Data Analytics, or a related field from an accredited college or university preferred. Equivalent combination of education, professional certifications, and relevant work experience will be considered.
Five (5) years of related experience or an equivalent combination of education and experience required.
Experience performing business analysis, requirements definition, or supporting product delivery required.
Experience delivering product capabilities for data analytics, business intelligence (BI), or other enterprise software platforms, whether commercial SaaS or internally built, required.
Strong product and requirements documentation skills.
Ability to translate business needs into detailed user stories and acceptance criteria.
Working knowledge of data analytics concepts such as data models, KPIs and metric definitions, dashboards, and self-service analytics.
Understanding of how AI-powered features are evaluated, including accuracy, reliability, and explainability of outputs.
Familiarity with agile delivery practices and backlog management.
Ability to assess scope, dependencies, and delivery complexity.
Strong analytical, problem-solving, and organizational skills.
Experience tracking delivery metrics and supporting OKR reporting.
Ability to understand and communicate budget impacts and delivery trade-offs.
Excellent verbal and written communication skills, including the ability to explain technical and AI concepts to non-technical audiences.
Strong cross-functional collaboration and stakeholder management skills.
Genuine curiosity and enthusiasm for using AI to change how people work with data.
Ability to meet or exceed performance competencies.

Nice To Haves

Experience supporting AI, machine learning, generative AI, or data-driven product initiatives preferred.
Experience in claims, insurance, healthcare, or other regulated operational environments preferred.
Experience working within agile or hybrid delivery teams preferred.

Responsibilities

Partners with Product Managers on backlog refinement and prioritization for the analytics platform, sequencing work based on user value, data dependencies, technical complexity, and capacity.
Defines development-ready stories and requirements by breaking down epics and features into user stories, defining acceptance criteria, and documenting data requirements, metric definitions, and high-level non-functional requirements such as performance, security, data access, and auditability.
Executes delegated Product Manager responsibilities when PM capacity or capability is limited, ensuring continuity of product execution.
Collaborates with engineering, data engineering, and analytics teams to ensure stories are well understood and aligned with business outcomes.
Validates solutions for business units by participating in and supporting User Acceptance Testing, including verifying the accuracy of data outputs, reports, and AI-generated insights against source data and defined acceptance criteria.
Provides visibility into delivery and outcomes by tracking and reporting on delivery progress, platform adoption, and user engagement to surface risks, dependencies, and performance insights for stakeholders.
Partners with Data Scientists, ML Engineers, and MLOps teams to translate AI/ML and generative AI capabilities into backlog items, defining acceptance criteria that account for model behavior, response accuracy, explainability, data dependencies, and performance thresholds.
Champions the user experience by gathering feedback from analysts, operational leaders, and business users to understand how they find, interpret, and act on data, then turns those insights into product improvements.
Partners with data governance, privacy, and security teams to ensure platform features align with data access controls, regulatory requirements, and responsible AI standards.
Raises risks, capacity concerns, and reallocation recommendations to Product Managers.
Supports sprint ceremonies by clarifying requirements and answering questions during delivery.
Supports product demos, walkthroughs, and stakeholder communications, helping business partners see what's possible with AI-powered analytics.
Serves as a subject matter resource for platform workflows, data sources, and capabilities.
Monitors deployed AI features for performance, accuracy, drift, and user feedback, and works with technical teams to surface retraining, tuning, or prompt refinement needs as backlog items.
Stays current on emerging trends in AI, generative AI, and modern analytics tools, bringing forward ideas that keep the platform ahead of the curve.
Performs other duties as assigned.