Data Analyst

Position Summary:
We have an exciting opportunity to join our team as a Data Analyst.

We are seeking a motivated Data Analyst to support medical imaging research and healthcare data processing projects at CAI2R, NYU Langone Health. The Data Analyst will work closely with an interdisciplinary team of imaging scientists, engineers, clinicians, and research staff to organize, process, analyze, and visualize imaging and clinical datasets.
This position is ideal for a candidate with strong quantitative, programming, and data-management skills who is interested in medical imaging, open-source research tools, and the clinical translation of imaging biomarkers.

Job Responsibilities:

Manage, organize, and analyze large medical imaging and healthcare datasets, including MRI/DICOM data and associated clinical or research metadata.
Develop and maintain scripts and workflows for data cleaning, quality control, harmonization, and statistical analysis.
Support quantitative imaging analyses across CAI2R platforms and research projects, including tools such as GRAVIS, mercure, and Yarra.
Generate tables, figures, visualizations, and summary reports for manuscripts, abstracts, grants, presentations, and internal project reviews.
Assist with validation, documentation, and reproducibility of image-processing and data-analysis pipelines.
Work with faculty, research scientists, engineers, and clinical collaborators to define data requirements and implement analysis plans.
Maintain project documentation, data dictionaries, analysis logs, and code repositories.
Support open-source dissemination by contributing documentation, example workflows, and user-facing materials.
Participate actively in regular project meetings and communicate findings clearly to technical and non-technical audiences.

Minimum Qualifications:
To qualify you must have a Minimum of 2 years of relevant research, data analysis, or programming experience.

Preferred Qualifications:
Masters degree in a relevant field, such as data science, biomedical engineering, computer science, statistics, biostatistics, epidemiology, applied mathematics, physics, or a related quantitative discipline.
Minimum of 2 years of relevant research, data analysis, or programming experience.
Strong programming skills in Python; experience with R, MATLAB, or shell scripting is a plus.
Experience working with large, complex datasets and developing reproducible analysis workflows.
Familiarity with statistical analysis, data visualization, and quality-control procedures.
Experience with version control tools such as Git.
Excellent organizational, time-management, and communication skills.
Ability to work independently and collaboratively in a dynamic interdisciplinary research environment.