Analyst II - Information Management, AI Governance

NYU Grossman School of Medicine is one of the nation's top-ranked medical schools. For 175 years, NYU Grossman School of Medicine has trained thousands of physicians and scientists who have helped to shape the course of medical history and enrich the lives of countless people. An integral part of NYU Langone Health [http://nyulangone.org], the Grossman School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care. At NYU Langone Health, equity and inclusion are fundamental values. We strive to be a place where our exceptionally talented faculty, staff, and students of all identities can thrive. We embrace inclusion and individual skills, ideas, and knowledge. For more information, go to med.nyu.edu [http://med.nyu.edu/], and interact with us on LinkedIn [https://www.linkedin.com/company/nyulangonehealth/?viewAsMember=true], Glassdoor [https://www.glassdoor.com/Reviews/NYU-Langone-Health-Reviews-E121521.htm], Indeed [https://www.indeed.com/cmp/Nyu-Langone-Health/reviews], Facebook [https://facebook.com/NYUSchoolofMedicine], Twitter [https://twitter.com/nyuschoolofmed] and Instagram [https://instagram.com/nyuschoolofmed]. Position Summary: We have an exciting opportunity to join our team as a Analyst II - Information Management, AI Governance. The AI Governance Analyst supports the safe, legal, and responsible development of AI/ML applications across NYU Langone Health. This role leads the intake of AI governance reviews, coordinates the review and preparation of risk reports and recommendations, supports submissions for AI/ML governance reviews, and communicates decisions. In addition, this role develops tools and processes that strengthen governance practices and lifecycle monitoring. The analyst acts as a bridge between mission areas, technical teams, and AI/ML governance at NYU Langone Health, promoting transparency, accountability, and alignment with institutional policies and national frameworks such as the NIST AI RMF and NYS-P24-001. Job Responsibilities: AI Intake & Processing - 40% Guide staff through the full lifecycle of AI/ML use case intake, including submission support, intake training, and lifecycle tracking. Support risk assessments and governance reviews by scheduling key stakeholders, maintaining intake logs, organizing use case materials, and preparing committee materials. Coordinate with enterprise teams to maintain a robust AI/ML inventory across pilot, production, and retirement phases. Ensure completeness and accuracy of intake records and documentation, leveraging automated tracking tools and, in some cases, structured data formats. Preferred: Use tools such as Python or SQL to support intake analytics, metadata quality checks, and validation readiness. Cross Functional Committee & Stakeholder Communications - 20% Serve as an AI/ML governance liaison between clinical, research, operational, and engineering teams, ensuring transparency across the full AI lifecycle. Prepare comprehensive AI/ML documentation packages for review, including use case summaries, risk triggers, evaluation outputs, and validation evidence. Support committee presentations by translating technical model details into digestible insights for diverse stakeholders. Communicate governance decisions, required actions, and timelines with clarity and accountability. Participation in Development of AI/ML Tools for NYULH - 20% Participate in document and share tools that enhance AI/ML governance, including tracking dashboards, model evaluation utilities, and monitoring templates. Monitor and maintain centralized governance systems tracking intake status, model health, and audit trails. Use technical skills (Python, SQL, JSON) to automate and scale governance functions and testing/validation methods. Partner with data engineers and domain experts to co-design training materials and technical infrastructure that promote sustainable, legal, and ethical AI use across NYULH. Controls, Benchmarking, & Monitoring Support - 20% Maintain best-practice templates and reference materials for: * Risk mitigations and safeguard implementation * Benchmarking and monitoring calculations using metrics like ROC-AUC, F1 score, and precision/recall * Calibration and drift-detection planning * Data quality and output control protocols * Algorithmic bias assessments Collaborate with data science and informatics teams to integrate monitoring logic using Python, SQL, or R. Provide operational support for annual reviews, model audits, and subgroup performance assessments. Apply familiarity with evaluation methods and NIST AI RMF to ensure risk model oversight. Minimum Qualifications: * 1+ years of experience in data engineering, data analysis, or applied informatics, with demonstrated ability to translate technical work into operational impact * Bachelor's degree in data science, mathematics, engineering, bioinformatics, or a related field; or equivalent combination of education and relevant experience * Proficient in Python, SQL, R, and JSON, with hands-on experience supporting data pipelines, controls monitoring, and audit workflows * Strong grasp of machine learning evaluation metrics, including ROC-AUC, F1 score, precision/recall, calibration curves, and other benchmarking methods used in comparative model analysis * Experience working with structured templates and tools to support monitoring, bias auditing, explainability, and validation across the AI lifecycle * Deep commitment to ethical AI, transparency, and lifecycle stewardship ensuring models remain accurate, accountable, and aligned with institutional and public trust * Ability to collaborate across diverse teams with strong organizational and communication skills * Familiarity with AI oversight f rameworks including NIST AI RMF, NYS-P24-001, and OMB M-24-10 Qualified candidates must be able to effectively communicate with all levels of the organization. NYU Grossman School of Medicine provides its staff with far more than just a place to work. Rather, we are an institution you can be proud of, an institution where you'll feel good about devoting your time and your talents. At NYU Langone Health, we are committed to supporting our workforce and their loved ones with a comprehensive benefits and wellness package. Our offerings provide a robust support system for any stage of life, whether it's developing your career, starting a family, or saving for retirement. The support employees receive goes beyond a standard benefit offering, where employees have access to financial security benefits, a generous time-off program and employee resources groups for peer support. Additionally, all employees have access to our holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care. The benefits and wellness package is designed to allow you to focus on what truly matters. Join us and experience the extensive resources and services designed to enhance your overall quality of life for you and your family. NYU Grossman School of Medicine is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. We require applications to be completed online. View Know Your Rights: Workplace discrimination is illegal [https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf]. NYU Langone Health provides a salary range to comply with the New York state Law on Salary Transparency in Job Advertisements. The salary range for the role is $70,481.61 - $106,180.20 Annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits. To view the Pay Transparency Notice, please click here [https://cdn-static.findly.com/wp-content/uploads/sites/290/2017/04/pay-transp_formattedESQA508c.pdf]