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Supports medical device packaging engineering for new product development and existing product improvements. Designs and analyzes packaging systems and materials, gathers user requirements, investigates field issues, performs root cause analysis, conducts testing, and creates DHF and DMR documentation. Participates in project teams, ensures quality and regulatory compliance, develops packaging concepts, supports process and material initiatives, and may submit invention disclosures.

The Senior Sales Operations Analyst calculates sales quotas, analyzes performance metrics, builds dashboards and reports, improves processes through automation, and supports territory planning, headcount management, and account alignment. The role partners with Sales, Marketing, Finance, IT, and Commercial Enablement teams, ensures sales-data accuracy and governance, translates complex data into executive insights, and recommends scalable technology and workflow improvements.

Drive sales operations through quota allocation, performance analysis, dashboards, reporting, AI, automation, data governance, territory planning, and process improvement. Partner with Sales, Marketing, Finance, IT, and analytics teams to develop scalable self-service solutions, evaluate emerging technologies, and translate complex data into executive recommendations that improve sales productivity and decision-making.

Leads the systems design function for active implantable medical devices, managing engineers and overseeing system requirements, architecture, integration, and product lifecycle development. Responsibilities include recruiting and developing talent, ensuring design control and quality compliance, guiding technical decisions, managing budgets and resources, leading cross-functional partnerships, and presenting strategic recommendations. The role requires extensive engineering leadership, regulated-industry experience, medical device development expertise, and knowledge of systems engineering methods.

Supports global sourcing teams through spend analytics, reporting, dashboards, supplier and category performance analysis, pricing analysis, data governance, and process improvement. The role develops actionable insights, maintains sourcing data, supports RFPs and negotiations, researches suppliers and markets, automates reporting, and contributes to sourcing technology implementations. It partners with cross-functional stakeholders and manages recurring and ad hoc analytics deliverables.

Owns the SAP SuccessFactors Onboarding 2.0 module, including configuration, workflows, business rules, issue resolution, release management, testing, governance, and process optimization. Partners with HR, Talent Acquisition, IT, Shared Services, and vendors to deliver onboarding enhancements, support mergers and acquisitions, maintain data integrity, and improve employee experience. The role also evaluates AI opportunities, manages system changes, and translates business needs into technical solutions.

Support AI, machine learning, and generative AI projects from exploration through delivery. Develop and evaluate models using data science and machine learning techniques, prototype AI solutions and GenAI agents, and collaborate with experienced developers and data scientists through coding, reviews, and team discussions. The role provides hands-on experience building AI solutions for real-world healthcare applications.

Develops and implements compensation and benefits programs, conducts market and job evaluations, analyzes pay data, advises HR and management, manages vendors and regulatory requirements, resolves escalated total rewards issues, and leads related initiatives across APAC. The role supports manufacturing and commercial populations and may cover health and welfare, executive compensation, sales compensation, equity, base pay, and incentive programs.

Develop and deploy AI-enabled applications for global supply chain and sourcing workflows. Translate ambiguous business needs into production-ready applications, pipelines, ontology objects, validation logic, and technical documentation. Build and test solutions using AI agents and LLMs, troubleshoot data and system issues, support user acceptance and production validation, and partner with business stakeholders, data teams, product owners, and external technical resources to deliver maintainable enterprise systems.

Develop and deploy AI-enabled applications for global supply chain and sourcing workflows. Translate ambiguous business needs into production-ready applications, data pipelines, ontology objects, validation logic, and technical documentation. Build and troubleshoot AI agents and LLM solutions, integrate data and models, validate application behavior with stakeholders, support user acceptance testing, and resolve post-deployment issues. Collaborate with product owners, subject matter experts, data teams, and external technical partners to deliver scalable, maintainable solutions in a regulated environment.