Data Harmonization Analyst at NYU Langone Health

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Aug, 26

Salary

126991.52

Posted On

15 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Harmonization, ETL Functional Requirements, Source-to-Target Mapping, Python, R, Machine Learning, SQL, NoSQL, Big Data, Biomedical Informatics, Data Quality Assurance, FAIR Data Principles, OMOP Common Data Model, Terminology Alignment, Predictive Modeling, Software Engineering

Industry

Hospitals and Health Care

Description

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 Data Science Analyst/Engineer. As part of the Complement-ARIE program, the NYU-Sage New Approach Methodologies (NAMs) Data Hub and Coordinating Center will create a controlled access platform for researchers to share and analyze data resulting from NAMs approaches. The program will build tools to standardize and harmonize NAMs data, store it securely, and provide researchers with powerful analytical and visualization tools. The successful candidate will support implementation of integrated standards [SG1.1]tailored for NAMs data. This position focuses on analyzing source data structures, developing source-to-target mapping specifications, authoring ETL functional requirements and data quality assurance frameworks, and ensuring that harmonization workflows are well-defined, reproducible, and aligned with FAIR data principles. The role is analytical and specification-oriented: the Data Analyst designs and documents the logic that guides implementation, rather than executing engineering tasks directly. Job Responsibilities: * Analyze source NAMs datasets (such as transcriptomics, proteomics, microscopy, imaging, electrophysiology, etc.) to characterize data structure, content, and quality prior to harmonization * Develop detailed source-to-CDM mapping specifications, including transformation rules, value set crosswalks, and handling of edge cases * Author functional ETL requirements and data flow documentation to guide pipeline development by engineering staff * Design data quality assurance (QA) frameworks and acceptance criteria for NAMs datasets, including completeness, conformance, and plausibility checks * Evaluate and document terminology alignment across existing Vocabularies, Metadata requirements, and source ontologies * Conduct mapping gap analyses and propose remediation strategies for non-standard or missing terminology coverage * Collaborate with the Lead Metadata and Standards Specialist to ensure mapping outputs align with metadata standards * Produce and maintain clear analytical documentation: data dictionaries, mapping catalogs, QA specification sheets, and implementation guide * Support onboarding of new data contributors by reviewing their data structures and advising on harmonization pathways * Participate in data quality review cycles, analyze QA outputs, and document findings and recommended remediation steps Minimum Qualifications: To qualify you must have a Masters degree in a quantitative discipline (Biomedical Informatics, Computer Science, Machine Learning, Applied Stascs, Mathematics or similar field) and 3 years of experience in machine learning/ data science. Proficiency in at least one programming language (Python, R) and machine learning tools (scikitlearn, R) Knowledge of predictive modeling and machine learning concepts, including design, development, evaluation, deployment and scaling to large datasets Familiarity with computing models for big data Hadoop / MapReduce, Spark etc. Knowledge of databases (Relational / SQL, NOSQL MongoDB etc.) Good grasp of soware engineering principles. Experience in integrating modern software architectures. Knowledge and some experience in operational aspects of soware development and deployment, including automation, testing, virtualization and container technology Knowledge of clinical and operational aspects of healthcare delivery. Excellent written and oral communication skills for a variety of audiences Preferred Qualifications: Experience with OMOP Common Data Model or other biomedical research CDMs Experience with programming languages (Python, JAVA, R) Familiarity with healthcare or life sciences data standards (UMLS, SNOMED-CT, LOINC), or sequencing data standards (FASTQ, BAM, VCF), etc. Knowledge of FAIR data principles and metadata standards Familiarity with NAMs methodologies or preclinical research data Experience with federated data networks or distributed query systems Familiarity with AI/ML tools applied to terminology matching, automated mapping recommendations, or data quality assessment 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 $84,577.93 - $126,991.52 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]

Responsibilities

The analyst will design and document the logic for harmonizing NAMs datasets, including creating source-to-target mapping specifications and ETL functional requirements. They will also develop data quality assurance frameworks and ensure alignment with FAIR data principles and metadata standards.