Research Data Analyst

Vanderbilt University Medical Center•Nashville, TN

1d•Onsite

About The Position

Vanderbilt University Medical Center (VUMC) is seeking a motivated and collaborative Data Analyst to support translational research programs focused on amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and related neurodegenerative diseases. This role offers a unique opportunity to work within a rapidly growing multidisciplinary research environment that integrates clinical research, biospecimen collection, biomarker discovery, multi-omics data analysis, and precision medicine approaches. The Data Analyst will work closely with clinicians, scientists, bioinformaticians, trainees, and research staff to support data-driven discovery efforts aimed at improving diagnosis, disease stratification, and therapeutic development for ALS and FTD. The Data Analyst will assist with the management, integration, analysis, and visualization of complex research datasets generated across multiple translational research studies and clinical programs. The position will support projects involving clinical metadata, longitudinal patient outcomes, genomics, epigenomics, transcriptomics, proteomics, and fluid biomarker datasets. The ideal candidate is detail-oriented, highly organized, analytically driven, and comfortable working with large-scale human research datasets in a collaborative academic research setting.

Requirements

Bachelor’s or Master’s degree in Data Science, Biostatistics, Bioinformatics, Computational Biology, Epidemiology, Computer Science, Biomedical Engineering, Public Health, or a related quantitative field.
Experience with statistical programming and data analysis.
Experience working with large datasets and relational databases.
Strong analytical, organizational, and problem-solving skills.
Excellent written and verbal communication skills.
Ability to work independently and collaboratively within a multidisciplinary team environment.

Nice To Haves

Experience analyzing biomedical, clinical, omics, or neurodegenerative disease datasets.
Familiarity with longitudinal clinical data and human subject's research.
Experience with multi-omics data analysis, including epigenomics and other high-dimensional molecular datasets.
Experience with REDCap, SQL databases, cloud computing environments, or high-performance computing systems.
Experience with data visualization tools and publication-quality figure generation.
Knowledge of genomics, epigenomics, transcriptomics, proteomics, biomarker studies, or multi-omics integration approaches.
Prior experience in academic medical center or translational research environments.
Machine learning approaches (preferred but not required)
Git/GitHub or version control systems

Responsibilities

Organize, curate, harmonize, and maintain large and complex clinical and research datasets from multiple ongoing studies and collaborations.
Perform data cleaning, quality control, validation, and integrity assessments across multimodal datasets.
Integrate clinical, molecular, biospecimen, and longitudinal patient data into standardized analytical frameworks.
Assist with database organization, REDCap management, and biospecimen tracking systems.
Perform statistical analyses and exploratory data analyses using R, Python, SQL, and/or related analytical platforms.
Support biomarker discovery, patient stratification, longitudinal modeling, and outcome association analyses.
Assist investigators with study design, data interpretation, and preparation of analytical plans.
Contribute to reproducible analytical workflows and pipeline development.
Generate publication-quality figures, tables, dashboards, and graphical summaries for manuscripts, presentations, grant applications, and internal reports.
Prepare analytical summaries for multidisciplinary research meetings and collaborative projects.
Assist with generation of reports for regulatory, consortium, and funding requirements.
Work closely with investigators, clinicians, laboratory personnel, trainees, and external collaborators across translational research projects.
Participate in multidisciplinary team meetings and contribute to scientific discussions and project development.
Support collaborative efforts across clinical, laboratory, and computational research teams.
Ensure compliance with institutional policies, HIPAA regulations, IRB protocols, and NIH data-sharing requirements.
Maintain secure handling of sensitive human subject and clinical research data.
Contribute to documentation, data dictionaries, standard operating procedures, and workflow organization.