TECHNICAL LEAD RESEARCH INFORMATICS

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The Technical Lead, Research Informatics provides senior technical leadership for enterprise research data and analytics platforms supporting Montefiore Health System and Albert Einstein College of Medicine

Technical Architecture and Platform Leadership

• Define and maintain the technical architecture for research informatics platforms, ensuring scalability, performance, and sustainability.
• Lead design decisions across:
  • Epic Cogito (Clarity/Caboodle) research environments
  • Epic Cosmos data integration and optimization
  • OMOP and other research data models
  • Cohort discovery tools
  • Research dashboards and analytics platforms
• Ensure interoperability across EHR, research, and enterprise data systems.

Project Management & Coordination

• Support the AVP of Research Informatics in planning and executing multiple data innovation initiatives, ensuring milestones, deliverables, and priorities are met.
• Coordinate with Health Research, Montefiore IT, and external collaborators to align projects with institutional goals and regulatory requirements.
• Serve as a primary liaison for project communications, translating research and operational needs into actionable technical requirements.
• Maintain centralized project tracking systems and comprehensive documentation, including project plans, reports, and meeting summaries.
• Facilitate stakeholder engagement through effective meeting coordination, progress reporting, and follow-up communication to ensure accountability.

Operational Support

• Assist with workflow optimization, including project intake, resource allocation, and reporting on operational metrics.
• Facilitate cross-training and knowledge-sharing activities within the Health Research Informatics team to promote continuity and role coverage.
• Prepare materials for leadership updates, stakeholder meetings, and quarterly reports.

Technical Product Delivery and Research Data Platforms

• Translate research and operational requirements into detailed product specifications, user stories, and technical requirements.
• Maintain comprehensive product documentation, architecture diagrams, and data dictionaries.
• Partner with data engineers and analysts to ensure high-quality, performant, and scalable research data assets.
• Collaborate with data analysts, engineers, and informatics staff to define project scopes, ETL specifications, and testing plans.
• Lead product governance for research data environments, including data access models, exclusion criteria, and audit processes.
• Ensure alignment with institutional privacy, security, and regulatory standards.
• Support the implementation and maintenance of cohort query tools, Epic databases, OMOP, and other research data systems.
• Lead and support projects leveraging Large Language Models (LLMs) in clinical and medical research-such as automating data extraction from pathology and clinical notes, improving cohort identification, and integrating AI tools into research workflows.
• Ensure adherence to data privacy, security, and ethical standards in all AI- and LLM-related initiatives.
• Collaborate on the development of user documentation, training materials, and standardized workflows to enhance researcher experience and system usability.

Required:

• Bachelor's degree in Health Informatics, Computer Science, Public Health, Information Systems, or a related field.
• 3+ years of experience in healthcare, research data management, or IT project coordination.
• Strong organizational skills with experience managing multiple projects in a fast-paced, matrixed environment.
• Familiarity with EHR systems (preferably Epic) and healthcare data models.
• Working knowledge of project management methodologies (Agile or Waterfall).
• Strong written and verbal communication skills with the ability to interface with both technical and non-technical audiences.
• Proficiency in productivity and collaboration tools.

Preferred:

• Epic certifications, including Clarity Data Model and advanced Epic implementation certifications
• Certification or coursework in project management (PMP, CAPM, or Agile/Scrum).
• Familiarity with institutional review processes (IRB, QI) and research data governance.
• Strong SQL querying skills and experience developing ETL specifications for data processing.
• Familiarity with machine learning and AI tools, particularly those used for healthcare predictive analytics and bio-surveillance.
• Experience implementing ML/AI based tools within institution's clinical workflows
• A PhD or equivalent advanced degree in a relevant field may substitute for some experience requirements.

• Strong attention to detail and ability to manage competing priorities.
• Excellent interpersonal and communication skills.
• Analytical and problem-solving mindset.
• Collaborative, team-oriented, and adaptable to change.
• Commitment to advancing data-driven research and healthcare innovation.