Pager Health

Marketing

• Advance and steward Pager Health’s visual brand identity across marketing and sales channels, ensuring consistency and alignment with our evolving market position.
• Create high-impact visual narratives for digital marketing, executive presentations, sales enablement materials, social media, thought leadership, video/motion, and web.
• Partner with Marketing and Sales to refine messaging and architect persuasive presentation stories for buyers and RFP responses.
• Translate complex and data-heavy healthcare and AI concepts into clear, compelling visuals, including charts, diagrams, frameworks, and infographics.
• Develop scalable templates, visual systems, and storytelling frameworks that improve speed, quality, and consistency across teams.
• Own management of the design and media library, maintaining quality control and version integrity.
• Support Growth and executive leadership with polished, data-driven presentations for internal strategy and external stakeholder engagement.
• Provide graphic design support for member engagement, including client-branded assets across email, digital assets, and direct mail
• Introduce modern design approaches and leverage emerging tools, including AI-enabled software, to increase efficiency and creative impact.

Brand and Creative Marketing Designer

Data Scientist

• Lead the design, development, deployment, and optimization of machine learning, predictive analytics, and AI-powered solutions.
• Translate business challenges and opportunities into analytical approaches, model specifications, and measurable success criteria.
• Apply advanced statistical analysis, machine learning techniques, and data science methodologies to solve complex business problems.
• Analyze large, complex datasets to identify trends, patterns, opportunities, and actionable insights.
• Develop and maintain model documentation, technical specifications, and implementation plans.
• Stay current with emerging technologies, tools, and best practices in data science, machine learning, and artificial intelligence.
• Design and execute comprehensive validation and evaluation strategies for machine learning and generative AI solutions.
• Develop benchmarking frameworks and success metrics to assess model performance, reliability, and business impact.
• Evaluate model quality using quantitative and qualitative measures, including accuracy, precision, recall, robustness, latency, and business outcome metrics.
• Assess generative AI applications for response quality, grounding, relevance, consistency, and hallucination risk.
• Identify and mitigate risks related to bias, fairness, explainability, privacy, and model reliability.
• Perform model validation, testing, and performance assessments prior to production deployment.
• Establish monitoring processes and evaluation methodologies to ensure continued model effectiveness and alignment with business objectives.
• Design, execute, and analyze experiments, including A/B tests and statistical studies, to measure product and business outcomes.
• Define key performance indicators and success metrics for machine learning and AI initiatives.
• Measure and communicate the impact of analytical solutions through statistical analysis and quantitative methods.
• Partner with stakeholders to define hypotheses, success criteria, and decision-making frameworks.
• Use experimentation and data-driven insights to guide product, operational, and strategic decisions.
• Collaborate with Engineering and Data Engineering teams to implement, operationalize, and scale models in production environments.
• Monitor deployed models for performance degradation, model drift, data quality issues, and changing business conditions.
• Recommend retraining, optimization, or replacement strategies based on model performance and evolving business needs.
• Support the creation of scalable, maintainable, and reliable AI and machine learning solutions.
• Ensure model deployment processes align with engineering best practices and operational requirements.
• Partner with Product, Engineering, Analytics, and business stakeholders to prioritize opportunities and deliver high-impact solutions.
• Communicate complex analytical findings and technical concepts to both technical and non-technical audiences.
• Present recommendations, insights, and model performance results to leadership and project teams.
• Support technical reviews, project planning, and delivery activities across cross-functional initiatives.
• Contribute to knowledge sharing, documentation, and best practices within the data science organization.
• Provide technical guidance and mentorship to junior team members and peers as needed.

Senior Data Scientist

Engineering Manager

• Manage complex technical projects in enterprise software from planning to delivery
• Drive career development, promotions, team management, and performance management.
• Collaborate and prioritize with tech leads and product managers in technical and product design to ensure high-quality product delivery.
• Partner with senior management to strategize and implement business goals.
• Recruit, mentor, promote, counsel, and nurture engineers at all levels including full stack and quality engineers of all levels.
• Prioritize and drive 20-30% of the backlog dedicated to technical improvement alongside feature development.
• Own KPI tracking and reporting for the team, including velocity, commit-to-complete ratio, and a balanced ticket mix across features, enhancements, defects, and technical debt.
• Identify opportunities for process improvement and lead initiatives for continuous improvement.
• Influence product priorities using technical knowledge to ensure efficient delivery while maintaining software health and performance.
• Facilitate and lead sprint ceremonies to foster communication, collaboration, and project momentum.
• Embrace AI tools while maintaining 'human-in-the-loop' validation to ensure quality.

Vice President

• Define and own Pager Health’s enterprise-wide data and reporting strategy.
• Establish a unified vision for how data is collected, governed, analyzed, and shared across the organization.
• Act as a strategic advisor to executive leadership, using data to identify opportunities.
• Build and lead a centralized Data and Reporting shared services function.
• Create clarity around ownership, operating model, priorities, and standards.
• Own enterprise-wide dashboards, KPIs, and measurement frameworks.
• Ensure effective use of data to drive business performance and operational efficiency.
• Oversee client-facing reporting and analytics delivery.
• Partner with Engineering and Product on data architecture and governance.
• Work closely with cross-functional teams to align data initiatives with business goals.
• Provide leadership and mentorship to data leaders and contributors.
• Manage and prioritize data initiatives, ensuring timely delivery of insights.
• Champion continuous improvement in data tooling and analytics rigor.
• Stay current on data trends and introduce new measurement approaches.

VP, Data, Analytics and Insights

Bilingual

• Provide non-clinical support to patients and members through virtual channels, including messaging, phone, and video, while delivering a high-quality service experience
• Support care coordination activities such as scheduling, follow-up outreach, resource connection, and resolving non-clinical barriers throughout the care journey
• Partner with nurses, providers, and operational teams to support inbound and outbound workflow needs and help ensure a seamless patient experience
• Recognize and escalate clinical concerns, symptom-related questions, urgent issues, or other needs requiring licensed staff in accordance with established workflows
• Troubleshoot real-time technology, access, or service issues that may affect the patient or member experience
• Support new workflows, operational initiatives, and other non-clinical duties as business needs evolve

Brand and Creative Marketing Designer

Senior Data Scientist

Engineering Manager

VP, Data, Analytics and Insights

Bilingual Care Coordinator – Per Diem