Senior Health Informatics Analyst

Albert Einstein College of Medicine•New York, NY

About The Position

As a member of the Health Research Informatics team in the Institute for Clinical and Translational Research (ICTR), the Senior Health Research Informatics Analyst will design, develop, and manage the data infrastructure that supports clinical and translational research across Einstein and Montefiore. The analyst will work closely with investigators, clinicians, data scientists, and IT professionals to ensure that research data systems are robust, scalable, and secure. The Senior Health Informatics Analyst will implement and manage health research information across several applications and data sources such as electronic medical records (EMRs), REDCap, WebCAMP, and the OMOP common data model, to enable analytics use cases and support a range of informatics projects. Responsibilities include formulating project scopes, documenting business requirements, developing data integration and quality monitoring strategies, and leveraging emerging technologies such as AI and data science tools. The successful candidate will demonstrate strong programming skills, critical thinking, and the ability to collaborate with investigators to provide excellent customer service that advances the institution’s research mission. Key contacts include CRIO, HRIC Co-Directors, Manager HRI, all other Research Informatics staff and the ICTR. Additionally, this role will interface with principal investigators and study teams as well as CTSA hubs and other external collaborators, as needed. This position does not directly supervise any personnel.

Requirements

Bachelor’s degree in informatics, computer science, data science, public health, or a related field.
3–5 years of experience in healthcare or biomedical research informatics
Proficiency in SQL and relational database design.
Experience working with EMR/clinical databases and research data warehouses.
Experience in data analysis, data mining or analytics
Experience with data management and integration tools such as REDCap, OMOP, or similar research data environments.
Excellent interpersonal and written communication skills to provide customer service and document user interactions and requirements
Strong analytical skills to analyze, categorize and translate business/user requirements to functional requirements
Demonstrated ability to take initiatives, establish/enhance business analysis procedures and improve operational efficiency
Collaborative mindset and adaptability in a fast-evolving research and technology environment.
Demonstrated commitment to innovation, continuous learning, and improving research data infrastructure.

Nice To Haves

Master’s degree in informatics, computer science, data science, public health, or a related field.
Experience with AI/ML tools, data science or cloud-based analytics platforms.
Familiarity with terminology systems and standards (e.g., SNOMED CT, LOINC, ICD).
Experience in biomedical research procedures and IT systems implementation.
Project and customer service management experience

Responsibilities

Work with investigators, project sponsors, and technical teams to define project objectives, data requirements, and analytic strategies aligned with institutional research goals.
De-identify, code, and manage clinical data in accordance with institutional policies, IRB protocols, and HIPAA regulations.
Facilitate secure data extraction, transformation, and delivery for approved research projects data access policies, de-identification standards, and secure data handling practices.
Review and validate data requests to ensure alignment with regulatory approvals and data-use agreements.
Maintain detailed documentation of data provisioning processes, approvals, and data lineage for audit and compliance purposes.
Design, document, and implement research informatics platforms, data pipelines, and infrastructure supporting clinical and translational research use cases.
Develop and maintain data workflows involving REDCap, EMR data sources, OMOP and various research data repositories and registries
Apply informatics principles for data management, governance, interoperability, and quality improvement initiatives.
Collaborate with research teams from other organizations and research consortiums
Support development of AI and data science solutions, including use of machine learning tools for data extraction, curation, and analysis.
Collaborate with institutional and external partners to standardize data models, ontologies, and metadata practices that enhance research reproducibility and data sharing.
Collaborate on topics around data quality, knowledge management, information representation and data governance
Train and support researchers on research information systems