Senior Data Analyst

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, 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, diversity, 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 diversity, inclusion, and individual skills, ideas, and knowledge. For more information, go tomed.nyu.edu, and interact with us onLinkedIn,Glassdoor,Indeed,Facebook,TwitterandInstagram.Position Summary:We have an exciting opportunity to join our team as a Senior Data Analyst.The NYU Langone Comprehensive Obesity Initiative is a new, institution-wide effort to better understand, treat and manage obesity at the population and clinical levels. The Initiative unites cutting-edge population health, clinical, and basic science research through a uniquely comprehensive electronic data source -- a multi-disciplinary DataBridge. This rich resource will enable investigators to address long-standing questions from completely new perspectives, using cutting-edge machine learning and other big data techniques. Key insights will be translated into real, evidence-based obesity prevention, treatment, and management solutions.This position helps to build and test a large, comprehensive repository for integration of diverse data pertaining to obesity (basic, clinical, and population sciences). Contributes to the creation of a user-friendly infrastructure that integrates and makes usable diverse and disparate data, and provides foundations for integration of advanced machine learning methods. Conducts wide-ranging analyses on these data, interprets and presents outcomes.Job Responsibilities:Cultivate deep familiarity with methodological approaches and data from diverse sources including big data platforms, large administrative databases, small-scale survey data, clinical and basic science, and others, and work to construct a database integrating them together.Assist in writing and editing manuscripts for publication.Conduct relevant literature reviews to inform cohort selection, variable definitions, and analytic methodsParticipate in data-driven decision making with investigatorsDevelop programs, methodologies, and files for analyzing and presenting data. Clearly communicate processes used and results achieved, and suggest new and alternative approaches.Suggest innovative solutions to data questionsMonitor, evaluate, and improve data quality. Detect and address issues in data, analytic results, and databases.Conduct comprehensive statistical analyses according to the study design (e.g., cross-sectional, time series, difference-in-difference, machine learning) and prepare sophisticated reports, charts and tables. Accurately and appropriately interpret and communicate resultsAdvanced programmingContinually manage ongoing additions to database. Import and clean raw datasets and create analytic datasets. Develop, manage, and improve databases to track provenance and versioning.Build and test large, comprehensive repository for integration of diverse data (basic, clinical, and population sciences).Minimum Qualifications:To qualify you must have:1. Masters in Data Science or equivalent combination of education and experience2. 5-6 years experience in database construction. We are open to considering advanced and early-career data scientists.3. Familiarity with major machine learning models and data mining techniques.4. Able to write code well in Python, R, or C++. Prior extensive experience with Python.5. Experience with SQL database design and operations. 6. Passion about being part of a team that solves big problems in health care.Preferred Qualifications:1. Familiarity with electronic health record databases.2. Familiarity with data driven modeling is a plus (including gathering and cleaning data, exploratory analysis, implementing models, error analysis, and presenting the findings)3. Comfortable with interfacing between database and python-pandas or other packages.4. Experience with a few machine learning open-source packages (such as sklearn)5. Excellent communication skillsQualified 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.NYU Grossman School of Medicine is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sex, sexual orientation, transgender status, gender dysphoria, national origin, age, religion, disability, military and veteran status, marital or parental status, citizenship status, genetic information or any other factor which cannot lawfully be used as a basis for an employment decision. We require applications to be completed online. If you wish to view NYU Grossman School of Medicine's EEO policies, please click here. Please click here to view the Federal 'EEO is the law' poster or visit for more information.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 $67,771.14 - $106,000.00 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

Created: 2024-10-19