• Job Type: Officer of Administration
• Bargaining Unit:
• Regular/Temporary: Temporary
• End Date if Temporary: 05/01/2027
• Hours Per Week: 35
• Standard Work Schedule:
• Building:
• Salary Range: $70,000 - $73,000

Position Summary

The Department of Obstetrics & Gynecology at Columbia University Irving Medical Center seeks a Temporary Data Analyst to support ongoing development of the genotype-phenotype repository. This position will assist with processing structured prenatal ultrasound data, generating standardized phenotype records, and supporting integration with genomic datasets for research purposes.

The Data Analyst will work closely with investigators and research staff to organize, standardize, and validate clinical and genomic data used in multi-institutional research collaborations. This role is focused on data preparation, quality control, and documentation to support genotype-phenotype research and federated data sharing initiatives.

This is a temporary position supporting an active research project.

Responsibilities

Data Processing & Phenotype Standardization – 45%

• Assist with extracting structured prenatal ultrasound data from system exports (JSON and HL7 formats).
• Support mapping of clinical findings to standardized Human Phenotype Ontology (HPO) terms.
• Generate phenopacket (v2 JSON) files using established workflows and templates.
• Perform quality control checks to ensure accuracy and completeness of phenotype data.
• Maintain clear documentation of data processing steps and data provenance.

Genotype-Phenotype Data Support – 25%

• Assist with organizing and preparing phenotype data for integration with genomic datasets (e.g., WGS/WES data).
• Conduct data cleaning, formatting, and validation to ensure consistency across datasets.
• Support routine data queries and assist with basic data joins under supervision.

Federated Data Infrastructure Support – 15%

• Assist with preparation and formatting of datasets for use in federated query systems.
• Support coordination with collaborating institutions to ensure consistent data formatting and schema alignment.

Research & Evaluation Support – 10%

• Assist with preparing datasets for evaluation studies comparing automated and manual phenotyping methods.
• Help prepare curated, de-identified datasets for approved AI/ML research activities.
• Support preparation of summary reports or figures as needed.

Administrative & Documentation Support – 5%

• Maintain organized project files and version control records.
• Contribute to technical documentation and standard operating procedures.
• Participate in team meetings and provide updates on assigned tasks.
• Perform other related duties and responsibilities as assigned/requested.

Minimum Qualifications

• Bachelor’s degree in Data Science, Computer Science, Bioinformatics, Public Health, Biology, or a related field; or equivalent combination of education and experience.
• Experience working with structured datasets (e.g., CSV, JSON).
• Basic programming experience in Python, R, or similar language.
• Strong attention to detail and organizational skills.
• Ability to follow established workflows and work collaboratively within a research team.

Preferred Qualifications

• Experience working with healthcare or clinical data.
• Familiarity with ontologies such as HPO or other standardized clinical terminologies.
• Basic understanding of genomic data (e.g., WES/WGS).
• Experience with data cleaning, validation, and quality assurance processes.
• Strong written and verbal communication skills.

The Department of Obstetrics and Gynecology is dedicated to the goal of building a multicultural faculty and staff committed to teaching, working and serving in a diverse community, and strongly encourages applications from candidates of traditionally underrepresented backgrounds.

We are continuously seeking to recruit individuals who will enhance the diversity of our workplace and the effectiveness of our organization.

Equal Opportunity Employer / Disability / Veteran

Columbia University is committed to the hiring of qualified local residents.