Job Description

Medical Information & Data Structuring Specialist

Brooklyn, NY | On-Site Preferred | Full-Time Preferred, 25+ hours considered | Salary: 80000-95000 DOE

Nonprofit medical referral organization seeks a highly organized, medically literate candidate to help research, organize, classify and structure complex medical information for internal database and projects. The candidate will work closely with leadership to support foundational medical information projects, including research, terminology standardization, metadata tagging, and quality review.

Required Qualifications

• Medical literacy: Ability to read and interpret medical literature and other medical information sources. Familiarity with medical specialties and clinical terminology.
• Data Literacy: Strong spreadsheet skills, including sorting, filtering, formatting, and organizing structured data.
• Excellent attention to detail, accuracy, and consistency.
• Thoughtful problem-solving within an internal framework.
• Experience using AI tools thoughtfully to support research, organization, workflow efficiency, with careful source verification and human review.
• Ability to turn messy or unstructured information into clean, usable data.
• Strong internet research skills and ability to distinguish reliable sources from weak ones.

Preferred Qualifications

• Experience with health information management, clinical research, medical librarianship, taxonomy, data operations, or healthcare data projects.
• Strong understanding of medical specialties, subspecialties, diseases, procedures, treatments, and terminology relationships.
• Experience with CRM systems, Salesforce, structured databases, or controlled vocabularies.
• Exposure to metadata tagging, classification systems, taxonomies, or structured knowledge systems.
• Clinical background, advanced health-science training, or strong healthcare research experience combined with strong data skills.

Strong candidates may come from backgrounds such as health information management, medical librarianship, clinical research, pre-med or health-science programs, public health, biology, neuroscience, healthcare data operations, or clinically experienced PA/NP/medical research environments.