Job Summary
Tech Product Owner: Required Experience (Healthcare Emphasis) 5+ years in technology product or platform product roles Demonstrated experience delivering healthcare technology products Direct exposure to healthcare data, analytics, or AI enabled solutions Experience operating in regulated environments (HIPAA, PHI, healthcare compliance) Proven ability to lead complex healthcare initiatives through ambiguity and change Healthcare Domain Expertise Strong understanding of healthcare operations and workflows, including payer, provider, and care management contexts Familiarity with healthcare domains such as: Utilization Management (UM) Care Management / Case Management Prior Authorization Ability to translate clinical and operational workflows into scalable technology solutions Deep appreciation for regulatory, compliance, and patient safety considerations in product decisions Product & Strategy Outcome driven product mindset grounded in healthcare realities and AI /data first thinking Ability to identify where data, analytics, and AI improve healthcare outcomes or reduce administrative burden Roadmap ownership integrating: Core healthcare capabilities Data and interoperability foundations Analytics and AI enablement Prioritization informed by clinical impact, operational value, feasibility, and risk Strong problem framing focused on insight generation, automation, and scale Data, Analytics & AI Enablement. Working understanding of: Healthcare data domains (member, provider, clinical, authorization, outcomes) Data flows across payer, provider, and partner systems Ability to partner with data engineering, analytics, and AI teams to: Enable reliable healthcare analytics and reporting Support decision making through insights and AI assisted summarization Experience defining requirements for: Operational and clinical dashboards KPIs tied to quality, efficiency, cost, and experience AI enabled analytics (summarization, prioritization, decision support) Awareness of data quality, lineage, interoperability, and adoption challenges in healthcare AI & Automation in Healthcare Understanding of AI use cases relevant to healthcare: Clinical and operational summarization Decision support (human in the loop) Workflow automation and prioritization Ability to balance innovation with: Responsible AI practices Explainability and auditability Regulatory and ethical considerations Experience guiding AI from pilot ? production ? scaled adoption in healthcare settings. Technology & Architecture Knowledge of modern architectures supporting healthcare data and AI: APIs, microservices, cloud platforms Data platforms, interoperability layers, and integration patterns. Ability to evaluate build vs buy vs reuse with healthcare constraints in mind. Comfort navigating legacy systems, technical debt, and complex integrations common in healthcare ecosystems. Delivery & Execution Agile / SAFe execution with emphasis on progress, readiness, and adoption. Strong dependency and risk management across:Product teams. Data pipelines. Analytics and AI platforms Release planning that includes: Data readiness and validation Analytics accuracy. AI model monitoring and compliance checks. Stakeholder & Communication. Trusted partner to business, clinical, and operations leaders. Clear articulation of tradeoffs, risks, and value realization
Acerca de Cognizant
Cognizant (Nasdaq: CTSH) es un creador de soluciones de IA y proveedor de servicios tecnológicos que conecta la inversión en IA con el valor empresarial mediante el desarrollo de soluciones de IA full‑stack para sus clientes. Su profundo conocimiento de la industria, junto con su experiencia en procesos e ingeniería, permite incorporar el contexto único de cada organización en sistemas tecnológicos que amplifican el potencial humano, generan resultados tangibles y mantienen a las empresas a la vanguardia en un entorno en constante cambio. Más información en cognizant.ai o @cognizant.
Información adicional sobre el empleo
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Cognizant es un empleador que ofrece igualdad de oportunidades. Su solicitud y candidatura no se evaluarán en función de la raza, el color, el sexo, la religión, el credo, la orientación sexual, la identidad de género, el origen nacional, la discapacidad, la información genética, el embarazo, la condición de veterano ni cualquier otra característica protegida por las leyes federales, estatales o locales.
