Data Analyst

NYU Langone Health • New York, NY

1d • $66,300 - $79,000

About The Position

The Center on Causal Data Science for Child and Adolescent Maltreatment Prevention (The CHAMP Center) seeks a data analyst to support its work determining predictive and causal models for child maltreatment exposures (e.g., physical abuse, sexual abuse, neglect) and outcomes (e.g., PTSD, depression, aggression). The aim of this work is to use these models to build clinical Decision Support Tools to prevent maltreatment and its consequences. The Data Analyst will join a team of data scientists, clinical scientists, and clinicians to build such models so they can inform clinical care. The candidate will have a central role on this team, preparing large real-world data sets for advanced computational analysis using state-of-the-art machine learning predictive classification, and causal data science methods. The Data Analyst will contribute to data pipeline development, database management, quality assurance, statistical analysis, reporting, and data sharing. This individual will work collaboratively with a diverse group of experts on internal and external teams to ensure timely, accurate, and reproducible analytic deliverables. The role also includes supporting research publications, presentations, funded programs, and grant-related reporting activities.

Requirements

• Masters degree in a relevant field such as biomedical sciences, physical sciences, public health, computer science, data science, biostatistics, or a related discipline
• At least 23 years of relevant experience in data analysis, data management, database systems, or research/clinical data environments
• Advanced knowledge of data analysis and data pipeline development
• Experience working with large, multimodal datasets from research databases
• Demonstrated ability to work independently, manage multiple tasks simultaneously, and proactively solve technical and logistical challenges
• Experience in managing data, manipulating data queries, and working with multiple databases.
• Strong communication skills and the ability to collaborate effectively with cross-functional teams.
• Proficiency in SPSS, Python, Excel, SQL, and database reporting tools
• Experience preparing reports, summaries, tables, and figures for research, clinical, operational, or funded program purposes
• Qualified candidates must be able to effectively communicate with all levels of the organization.

Nice To Haves

• Experience with machine learning, predictive analytics, and AI-enabled data workflows
• Experience supporting psychiatric research or other clinical research data
• Familiarity with data standardization, quality assurance processes, and reproducible analytic methods
• Experience contributing to manuscripts, presentations, and grant applications
• Knowledge of funded program reporting, compliance, and interdisciplinary collaboration

Responsibilities

• Develop data cleaning routines in alignment with program goals, working efficiently with internal and external teams
• Maintain accurate data dictionaries and code books
• Facilitate real-time data monitoring and interim analyses
• Create and execute plans for new data collection projects
• Maintain familiarity with new technologies for data management
• Provide support on multiple projects to meet timelines
• Create and perform system backups and recovery
• Collaborate with biostatisticians and machine learning experts to prepare data for advanced predictive and causal analyses
• Contribute to the development, validation, and maintenance of models in collaboration with data scientists and clinical investigators, and report and interpret results
• Integrate AI tools and platforms into data pipelines to automate quality checks and outcome forecasting
• Perform statistical analysis of medical and research data using SPSS, Python, Excel, SQL, or other relevant tools; generate data listings, tables, figures, and reports from clinical or operational datasets
• Contribute to the development, validation, and maintenance of models in collaboration with data scientists and clinical investigators, and report and interpret results
• Integrate AI tools and platforms into data pipelines to automate quality checks and outcome forecasting
• Perform statistical analysis of medical and research data using SPSS, Python, Excel, SQL, or other relevant tools; generate data listings, tables, figures, and reports from clinical or operational datasets
• Contribute to research design, methods, and results sections for research publications and grant applications
• Generate publication-quality figures for presentations and journals
• Promote consistency in analytic methods, documentation, and best practices across projects
• Prepare interim summaries and reports, and translate research questions into feasible analytic approaches
• Review and quality-check analytic outputs and code to ensure methodological rigor, reproducibility, and adherence to study protocols
• Assist in pipeline optimization, automation, and quality assurance activities.
• Process and analyze complex datasets, including large multimodal research data.
• Assist in database administration, code modifications, reporting support, and maintenance of data systems.
• Create ad hoc reports and summaries to support operational, research, and funded program needs.
• Contribute to data sharing, documentation, archival practices, and compliance with reporting deadlines and protocols.
• Adhere to ethical research conduct, confidentiality standards, and institutional procedures

Benefits

• financial security benefits
• generous time-off program
• employee resources groups for peer support
• holistic employee wellness program (physical, mental, nutritional, sleep, social, financial, and preventive care)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level