Paradigm Health

Director

• Implement Paradigm Software and Solutions workflows at our provider organizations, at scale
• Partner across product development, sales, customer success, engineering, informatics and data science to ensure seamless integration with EHR, Genomics Vendor and CTMS systems
• Manage implementations and track implementation timelines and capacity
• Develop and communicate a comprehensive implementation strategy aligned with company objectives and present updates to executive stakeholders
• Lead, mentor, and empower a team of implementation managers and specialists; manage escalations and risk mitigation
• Serve as primary liaison with key clients during implementation; define project scope, timelines, and deliverables; oversee multiple large-scale software deployments
• Establish and maintain quality assurance processes; define KPIs and metrics; conduct reviews and audits to identify improvements

Executive Director, Implementations

Clinical Research

• Trial Coordination &amp; Patient Enrollment: Oversee daily study operations, manage pre-screening, validate patient eligibility, and support smooth handoffs to sites for full screening and consent.
• Site Engagement &amp; Communication: Collaborate closely with site staff and investigators to optimize enrollment workflows, support feasibility assessments, and provide study updates.
• Data &amp; Compliance: Ensure accurate data collection, maintain patient confidentiality, and follow GCP, protocol, and regulatory standards.
• Product Feedback &amp; Platform Insights: Capture site-level and patient insights, track issues or improvement opportunities, and work with product/engineering teams to enhance the Paradigm platform, including NLP-driven features.
• Site Visits &amp; Training: Conduct site qualification visits as needed and support onboarding, training, and ongoing guidance for site teams.
• Mentorship &amp; Team Support: Guide junior CRCs, share best practices, and contribute to continuous improvement across the team

Clinical Research Coordinator

DevOps Engineer

• Infrastructure Development & Optimization: Architect and implement robust, scalable ML infrastructure that supports model training, deployment, and monitoring.
• ML Platform Engineering: Develop and maintain ML model serving and orchestration platforms, ensuring seamless integration with existing engineering workflows. Gitlab pipelines for software and machine learning engineering
• Data Pipeline and Feature Engineering: Design and optimize ETL/ELT pipelines for ML applications, enabling efficient and reliable data preprocessing and transformation.
• MLOps and Automation: Implement MLOps best practices to streamline model lifecycle management, from training to deployment, monitoring, and retraining.
• Cloud & Containerization: Leverage cloud computing resources (AWS, GCP) and container orchestration (Docker, Kubernetes) to scale ML workloads efficiently.
• Monitoring and Reliability: Develop advanced monitoring systems to track model performance, data drift, and infrastructure health.
• Security & Compliance: Collaborate with privacy and security teams to ensure compliance with regulatory standards and best practices for handling sensitive clinical data.
• Collaboration & Mentorship: Work closely with software engineers, data scientists, and ML engineers to align infrastructure with business and technical goals while mentoring junior engineers.
• Stay Current on Engineering and ML Infrastructure Trends: Keep up to date with advancements in ML platforms, distributed computing, and scalable ML systems, integrating innovative solutions into our ML ecosystem.

Executive Director, Implementations

Clinical Research Coordinator

Staff SW Engineer, DevOps/MLOps