Senior Database Analyst

NYU Grossman School of Medicine; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

NYU Grossman School of Medicine seeks a Senior Database Analyst to join the Digital Health and Computational Psychiatry Program in the Department of Psychiatry. You will design, develop, and maintain databases for complex clinical research, harmonize diverse datasets, and support predictive analytics with ML/AI techniques.

You will collaborate with biostatisticians and investigators, develop automated data pipelines, and ensure governance and HIPAA compliance across projects.

Qualifications

• Masters or PhD in Computer Science, Data Science, Biomedical Informatics or related field with 3+ years experience.
• Relational and non-relational databases, data pipeline development, and data standards.
• Proficiency in SQL, Python, R, SAS with statistical modeling and ML techniques.
• Understanding of clinical data governance, HIPAA, 21 CFR Part 11, and GCP.

Responsibilities

• Design, develop and maintain relational and non-relational databases for multimodal clinical research.
• Develop ETL routines, data dictionaries, and automated dashboards for real-time monitoring.
• Collaborate with biostatisticians and ML experts to prepare data for modeling and analytics.
• Apply ML/AI to healthcare datasets and validate models with governance controls.
• Ensure data security, access controls, and compliance with institutional and sponsor requirements.
• Mentor junior data analysts and provide data management support across projects.

Skills

SQL

Python

R

SAS

Data modeling

Machine learning

ETL

Data governance

Data visualization

Big data handling

Education

Masters or PhD in Computer Science, Data Science, Biomedical Informatics

Tools

MS SQL Server

MS Access

VBA

Tableau/Power BI

MATLAB

Python libraries (scikit-learn, TensorFlow, PyTorch)

Job description

Position Summary:

We have an exciting opportunity to join our team as a Senior Database Analyst.

The Senior Database Analyst will work in the interdisciplinary and cutting-edge Digital Health and Computational Psychiatry Program in the Department of Psychiatry. He/She will design, develop, and maintain relational and non-relational database systems to support complex, multimodal clinical research studies. This position requires deep expertise in data engineering, database architecture, clinical data standards, and research data governance. The ideal candidate will also leverage advanced data analytics, machine learning, and AI-driven techniques to support predictive modeling and translational research insights. The candidate will play a critical role in harmonizing diverse datasets across studies, supporting advanced statistical modeling and predictive analytics in psychiatric and translational research.

Job Responsibilities:

• Develop data cleaning, quality control and Extract Transform Load (ETL) routines
• Maintain accurate data dictionaries and code books
• Create automated dashboards, query tools, and reports to facilitate real-time data monitoring and interim analyses.
• Coordinate with NYU MCIT EDW team to make updates and correct data issues in data warehouse
• Create and execute plans for new data collection projects
• Ensure smooth integration of data from disparate sources
• Maintain familiarity with new technologies for data management
• Develop tools for temperature measurement in rodent and human systems
• Conduct testing in development database systems
• Troubleshoot IT problems at NYULMC, interfacing with MCIT EPIC and EDW teams as well as with external IT support personnel as needed.
• Ensure compliance with institutional, federal (e.g., HIPAA, 21 CFR Part 11), and sponsor-specific data governance requirements.
• Develop and implement departmental SOPs for data management
• Assist in managing the creation of user accounts and access permissions to folders and files,
• Provide support on multiple projects to meet timelines
• Perform system backups and recovery
• Produce data files for further analysis by statisticians
• Conduct queries and reports for basic statistical analysis for reporting purposes
• Generate and maintain codebooks and data dictionaries development of big database systems
• Ensure smooth integration of data acquired from disparate sources
• Design, maintain and update databases and data collection tools
• Collaborate with biostatisticians and machine learning experts to prepare data for advanced statistical modeling and predictive analytics
• Apply machine learning algorithms (e.g., clustering, classification, regression) to clinical datasets to uncover patterns and predict patient outcomes.
• Develop, validate, and maintain ML/AI models in collaboration with biostatisticians and clinical investigators.
• Integrate AI tools and platforms into data pipelines to automate quality checks, anomaly detection, and outcome forecasting.
• Utilize tools such as Python, R, and SQL to generate insights from structured and unstructured data.
• Design and implement advanced analytics workflows to support hypothesis generation, exploration analysis, and outcome prediction.
• Data summary and manipulation in consultation with senior level Biostatistician and Principal Investigators, conducting statistical analyses, and reporting and interpreting of results
• He/She will perform statistical analysis of medical research data, using SAS, R or other computer languages; generate data listings, tables, and figures from clinical data; write statistical reports for clinical studies
• Facilitate the development and application of adequate statistical methods in psychiatric research
• Conduct statistical analyses for research manuscripts for publication
• Conduct statistical power analyses for planning research projects
• Contribute to research design, methods, and results sections for research publications and grant applications
• Contribute to data management plans for grants and protocols, and support data sharing via platforms like dbGaP, NDA, and other repositories.
• Liaise with NYU IT, IRB, REDCap, and other institutional systems as needed to support data security and compliance.
• Ability to program data extraction codes and post-processing codes for data analysis in MATLAB or other computer languages
• Provide mentorship and oversight to junior data analysts and research assistants handling data entry, QA, or preprocessing tasks.
• Generation of publication quality figures for presentations and journals
• Other duties as assigned

Minimum Qualifications:

To qualify you must have a Masters or PhD degree in Computer Science, Data Science, Biomedical Informatics, or a related field with 3 or more years related experience or an equivalent combination of education and experience.
Advanced knowledge of relational and non-relational databases, database architecture, and data pipeline development.
Proficiency in SQL, Python, R, and SAS, with experience in applying statistical modeling, data analytics, and machine learning techniques.
Strong understanding of data management principles, including data collection, data flow, quality control, integration, archiving, and clinical data standards.
In-depth knowledge of clinical and research operations, including familiarity with FDA, ICH, HIPAA, 21 CFR Part 11, and GCP regulations as they relate to data systems and governance.
Experience developing and maintaining automated reporting tools and data dashboards for real-time analytics and monitoring.
Experience working with large, complex, multimodal datasets from structured assessments, electronic health records, and research databases.
Experience with data visualization tools such as Tableau, Power BI, or equivalent.
Working knowledge of AI/ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and their application in healthcare or research analytics is strongly preferred.
Experience managing and programming in MS Access and MS SQL Server, including Visual Basic for Applications (VBA)
Familiarity with Cardiff TELEform, LiquidOffice, and OCR-based data capture systems.
Experience with business intelligence platforms such as SAP BusinessObjects.
Ability to administer data security protocols, plan for system backup and recovery, and maintain data access controls.
Demonstrated ability to work independently, manage multiple tasks simultaneously, and proactively solve technical and logistical challenges.
Excellent organizational, interpersonal, and