Product Operations Analyst

McKesson•Irving, TX

3d•Hybrid

About The Position

The Product Operations Analyst will execute the definition of product performance tracking and portfolio insights and strategic reporting for the operating model across Pharmacy Management, Clinical Service and Inventory Optimization technology products. This role will be responsible for AI-forward product performance standards that drive customer experience and growth across products. This individual sits at the intersection of product operations, data, and engineering to drive product health reporting and performance dashboard infrastructure definition, visualization, and review cadences. Furthermore, this role will partner closely with Product, Data Insights, and Customer Success teams on portfolio-level metric level definition and synthesize customer insights to delineate data decisions that accelerate product delivery. Reporting to the Director of Product Operations & Strategy, this individual implements and refines data methodologies across the product organization. This role drives operational outcomes focused on actionable, evidence-based insights that guide product growth and business outcomes. This role works closely with Product Leadership, Engineering, Customer Success, Data Insights, Commercial teams and other McKesson organizations to drive our strategic objectives and operational efficiency and support business growth. McKesson Pharmacy System (MPS) is an independent business within the larger McKesson Commercial Strategy & Innovation (CSI) organization.

Requirements

Degree or equivalent and typically requires 4+ years of relevant experience.
4+ years of progressive experience in product management, product operations, technology consulting, analytics, or related technology transformation roles.
Strong experience with Claude, Rovo, Figma or equivalent AI-first product tools to accelerate product development.
Strong data analysis acumen with experience in Excel, SQL, R, Python or other comparable BI tools such as Power BI, Looker and Tableau.
Strong understanding of product metrics fluency, dashboard reporting infrastructure, and prioritization frameworks.
Strong organizational skills with the ability to collaborate with multiple, concurrent work streams and meet deadlines reliably.
Strong cross-functional facilitation and collaboration: able to engage product, engineering, data, design, customer success and commercial leaders, to influence conversations, mitigate issues / decisions, document outcomes, and drive accountability.
Strong analytical fluency governing product metric definitions, measuring product health, assessing product KPI taxonomy, and extracting insights from data within context in collaboration with cross-functional partners.
Clear written communication and storytelling skills with the ability to produce clean, readable documentation and leadership-ready narrative.
Comfortable coordinating across teams and following up on action items without formal authority.

Nice To Haves

Experience with AI/automation tools for product management and design workflow acceleration.
Experience supporting operating mechanisms for multi-product platform organizations where the operating model itself is a transformation deliverable.
Familiarity with technical product concepts, cloud platforms, data ecosystems, and API-driven models is beneficial.
Experience in healthcare, pharmacy operations, supply chain, or predictive analytics domains.

Responsibilities

Maintain and update the KPI taxonomy that defines how product health is measured and reported across the portfolio; use AI tools to ensure metrics are consistently defined and comparable while accommodating different business models.
Build and maintain product performance dashboards; coordinate with Engineering teams to ensure the underlying instrumentation, data access, and visualizations are accurate and current.
Craft templates and materials for product performance reviews; track the review cadence, follow up with PMs to collect inputs on schedule, and ensure submissions are grounded in data rather than qualitative narrative for executive audiences.
Monitor product performance data on a recurring basis to identify early-warning signals; flag risks to relevant leads and support the escalation process by pulling the right data and engaging the right stakeholders across Product, Engineering, and Customer Success.
Aggregate and analyze product performance data across the product portfolio using AI tools to accelerate pattern recognition and prepare evidence-based insights that inform resource reallocation, acceleration, or sunset recommendations.
Synthesize data across product areas into a coherent narrative for leadership and flag anomalies or emerging risks proactively.
Prepare executive summaries and KPI tracking templates; ensure all reporting is grounded in current data and formatted for the intended audience.
Aggregate VOC data using AI-powered analysis to surface themes and patterns at scale; collaborate cross-functionally to maintain the feedback taxonomy and routing process to ensure insights reach the right leaders.
Monitor the competitive landscape on a recurring basis; compile and summarize market intelligence, competitor product updates, and industry signals into impactful narratives that inform product and portfolio decisions.
Champion the use of AI to identify recurring gaps or inconsistencies in how performance data is collected and reported across the portfolio.
Execute and continuously evaluate the scoring process for the product prioritization framework.
Build core deliverables for PM training, onboarding, and enablement, leveraging AI to accelerate content development and refinement.
Prepare materials to support coaching of PMs on prioritization, ROI sizing, experimentation, and planning.
Support the administration of AI tooling that rapidly accelerates product operational workflows and reusable templates for product development.
Identify opportunities to embed AI into operational workflows and champion adoption of AI-powered productivity practices across the product organization.
Utilize AI-led tools and research concepts to capture critical data points regarding competitive landscape, customer needs, and market trends that influence decisions for the product strategy.
Monitor roadmap inputs and progress and identify key data points for opportunity areas to accelerate delivery across the product portfolio.