Press Ganey

Implementation Specialist

• Own and manage standard client onboarding projects for mid-market clients
• Serve as the day-to-day client contact, ensuring alignment on objectives, timelines, and deliverables
• Coordinate with cross-functional delivery teams to execute configurations, data integrations, and product deployments
• Identify project risks and issues early and collaborate with supervisors on resolution strategies
• Provide clear, proactive communication to clients and internal stakeholders
• Support clients in understanding workflows, product configurations, and training pathways
• Maintain accurate project plans, status reports, and documentation
• Contribute to process improvements by sharing feedback and supporting team initiatives
• Build foundational expertise in healthcare client environments, Qualtrics products, and implementation methodology

Associate Client Implementation Manager

Machine Learning Engineer

• Lead the design, delivery, and operation of production-grade AI systems
• Build services and high-throughput pipelines for a text analytics platform and AI products
• Own technical delivery from prototype through deployment and ongoing production support
• Partner with AI Scientists and Product to define requirements, plan implementation, and resolve cross-team dependencies
• Evaluate AI solutions for production suitability and identify technical risks
• Choose architectures meeting quality, reliability, and cost requirements
• Architect and build high-volume AI services and processing pipelines with fault tolerance, backpressure, retries, idempotency, and partial-failure recovery
• Lead the evolution of Python services and a Databricks-based platform for distributed processing, model serving, and ML/LLM integration
• Establish standards for automated testing, CI/CD, model and prompt versioning, load testing, controlled rollouts, and rollback
• Build evaluation and monitoring capabilities for AI quality regressions and service reliability, throughput, latency, and inference cost
• Partner with Product and Responsible AI teams on release criteria, model validation, data privacy, security, and governance
• Optimize processing and inference workloads for quality, throughput, latency, capacity, and cost
• Mentor engineers and lead architecture and code reviews

Staff ML Engineer

• Design, build, and deploy production-ready AI agents and agentic workflows integrated with enterprise applications and business processes
• Establish evaluation, monitoring, guardrail, and safety frameworks for LLM-powered applications
• Architect and implement scalable AI-enabled capabilities within the existing Java/Spring platform and distributed microservices ecosystem
• Establish engineering best practices for AI Agent systems, including observability, testing, deployment, versioning, and operational excellence
• Drive architectural decisions across AI services, microservices, APIs, and enterprise application integrations
• Collaborate with AI Scientists and ML Engineers to productionize models and translate experimentation into reliable software
• Mentor engineers, lead architectural reviews, and influence technical strategy across teams
• Evaluate emerging AI technologies and recommend pragmatic adoption strategies to improve product capabilities and developer productivity

• Build, test, and deploy production-ready AI agents and agentic workflows integrated with enterprise applications and business processes
• Implement evaluation, monitoring, guardrail, and safety frameworks for LLM-powered applications
• Develop and maintain AI-enabled features within the Java/Spring platform and distributed microservices ecosystem
• Collaborate with AI Scientists and ML Engineers to productionize models and translate experimentation into reliable software
• Stay current with emerging AI technologies and recommend pragmatic adoption strategies
• Incorporate feedback from specialists, tech-ops, and product managers
• Participate in design reviews, technical discussions, and requirement planning
• Attend daily stand-up meetings, collaborate with peers, prioritize features, and deliver customer value
• Prototype and test potential solutions to large problems

ML Engineer

Associate

• Lead analytics and insight development for consulting engagements focused on patient experience, member experience, quality improvement, operational excellence, and organizational transformation
• Translate complex datasets into clear, executive-level recommendations and strategic action plans
• Facilitate workshops, executive briefings, strategic planning sessions, and performance review meetings with senior healthcare leaders
• Partner with clients to design, implement, and sustain experience transformation initiatives
• Establish success metrics and measurement frameworks demonstrating engagement impact and return on investment
• Manage multiple client workstreams while ensuring exceptional quality and timely delivery
• Analyze Press Ganey and client datasets to identify performance trends, root causes, gaps, and improvement opportunities
• Develop dashboards, scorecards, presentations, and data visualizations supporting executive decision-making
• Leverage quantitative and qualitative insights to guide strategy development and operational improvement
• Collaborate with subject matter experts, analytics teams, and engagement leaders to validate findings and develop recommendations
• Identify leading indicators and performance drivers related to patient experience, quality outcomes, employee engagement, and operational effectiveness
• Build trusted relationships with healthcare executives, physician leaders, and operational stakeholders
• Serve as a strategic thought partner on experience improvement, culture transformation, and quality excellence initiatives
• Support opportunity identification, proposal development, solution design, and engagement scoping
• Contribute to client retention and expansion by delivering measurable value and identifying deeper partnership opportunities
• Partner with consultants, product leaders, project managers, and analytics teams across client engagements
• Promote best practices, knowledge sharing, and continuous improvement across the consulting organization
• Contribute to the evolution of consulting methodologies, tools, frameworks, and thought leadership

Associate Client Implementation Manager

Staff ML Engineer

Staff ML Engineer

ML Engineer

Associate Principal, Healthcare Consulting