Senior Manager Clinical Engineering Data Analytics

Gateway Recruiting; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Gateway Recruiting seeks a Senior Manager, Clinical Engineering & Data Analytics to build and lead a cross-disciplinary organization spanning Clinical Engineering, Data Warehousing, and Data Analytics, driving AI-enabled insights and best-in-class treatment planning capabilities across the business.

The role establishes a unified platform and strategy to translate clinical intent into measurable clinical, operational, and business outcomes, enabling scalable, data-driven solutions and outcomes.

Qualifications

• Bachelor’s degree in engineering, data science or related field.
• 8+ years in clinical engineering, digital health or data analytics.
• 5+ years of people leadership experience.

Responsibilities

• Lead and build multidisciplinary team across clinical engineers, data warehousing, data scientists and analytics professionals.
• Define strategy for data-driven clinical engineering, including roadmaps for analytics platforms, AI capabilities, and data infrastructure.
• Build and maintain scalable, cloud-native architectures that unify data sources for operational insights and clinical research.
• Develop capabilities for data-driven clinical outcomes using real-world data, modeling and AI/ML tools to improve treatment quality.

Skills

Data Analytics

Leadership

Cross-functional leadership

AI/ML

Data Warehousing

Cloud Platforms

Healthcare Analytics

Stakeholder Alignment

Communication

Agile

Education

Bachelor's degree in engineering/CS/related field

MS/PhD in engineering/data science/related discipline

Job description

Job Description:

This role provides an opportunity to build and lead a newly formed, cross-disciplinary organization spanning Clinical Engineering, Data Warehousing, and Data Analytics, with a mandate to deliver data-driven clinical engineering outcomes, AI-enabled insights, and best-in-class treatment planning capabilities across the business.

The Senior Manager, Clinical Engineering & Data Analytics will define, build, and scale an integrated capability that connects clinical science, digital platforms, advanced analytics, automation, and AI-enabled decisioning. This role will be accountable for translating clinical intent into measurable clinical, operational, and business outcomes, enabling insights and solutions that improve clinical efficacy, scalability, and portfolio differentiation.

Responsibilities will Include:

• Leading and developing a multidisciplinary team of clinical engineers, data warehouse engineers, data scientists, and analytics professionals, establishing a shared vision, operating model, and culture across disciplines
• Setting the strategic direction for data-driven clinical engineering, including ownership of roadmaps for treatment planning, analytics platforms, AI/ML capabilities, and data infrastructure in alignment with R&D and Business leadership
• Leading the team and strategy for building, evolving and maintaining scalable, cloud-native architectures that bring together multiple data sources into a unified platform, providing modular, scalable services and advanced analytics for operational insights and clinical research.
• Building and deploying capabilities for data-driven clinical outcomes, leveraging real-world data, modeling, simulation, advanced analytics, and AI/ML tools to improve treatment quality, predict outcomes, and reduce clinical variability
• Driving best-in-class treatment planning solutions, leveraging clinical expertise, advanced data analytics and predictive modeling to create translating clinical treatment goals that can be translated into scalable algorithms, AI-assisted workflows, and decision-support tools embedded within digital platforms
• Leveraging AI and machine learning to amplify the impact of the organization, delivering predictive and prescriptive insights that inform broader portfolio strategy, including product differentiation, workflow automation, and next-generation digital capabilities
• Critically collaborating and aligning with Digital and Automation teams to ensure clinical algorithms, analytics, and AI-enabled insights are translated into scalable, automated, and production-ready solutions, seamlessly integrated into end-to-end digital workflows
• Partnering closely with clinicians, customers, R&D, Digital, Regulatory, and portfolio teams to align priorities, integrate feedback, and ensure end-to-end deployment of solutions
• Measuring and communicating impact, defining clinical, operational, and business KPIs and clearly articulating value creation to senior leadership and key stakeholders
• Embedding a culture of innovation and accountability, encouraging evidence-based decision-making, appropriate risk-taking, and continuous learning across the organization

Skills and Expertise:

Required:

• Bachelor’s degree or higher (completed and verified prior to start) in engineering, data science, biomedical engineering, computer science, or a related scientific discipline
• 8+ years of experience in clinical engineering, digital health, data analytics, or related technical domains in a private, public, government, or military environment
• 5+ years of experience leading teams with deep technical expertise, including people leadership, organizational design, and talent development

Additional Qualifications:

• M.S. or Ph.D. in engineering, data science, biomedical sciences, or a related discipline
• Experience with clinical treatment planning, digital dentistry, dental devices, or regulated healthcare environments
• Demonstrated experience translating clinical or scientific problems into scalable, data-driven or digital solutions
• Strong understanding of analytics, modeling, simulation, and/or AI/ML methodologies applied to clinically informed or healthcare-adjacent problems
• Proven track record of cross-functional leadership, including stakeholder alignment, prioritization, and execution in matrixed organizations
• Hands-on experience with data warehousing, cloud data platforms, or enterprise analytics ecosystems
• Experience leading teams that apply AI and machine learning to clinical, scientific, or digital workflow problems with a focus on real-world deployment and measurable impact
• Demonstrated ability to translate AI/ML potential into prioritized clinical and business outcomes, avoiding exploratory or research-only approaches
• Leadership experience partnering with AI/ML specialists, automation teams, and digital product organizations to operationalize models into scalable, governed solutions
• Demonstrated experience providing researchers and operations teams with self-service BI, real-time dashboards, and high-fidelity datasets.
• Strong business acumen with the ability to connect technical investments to portfolio strategy and customer value
• Excellent communication skills with the ability to influence at senior leadership levels
• Decisive, comfortable with ambiguity, and skilled at balancing speed with rigor
• Agile, growth-oriented leadership mindset