Data Science Analyst/Engineer

NYU Langone Health • New York, NY

2h • $84,578 - $126,992

About The Position

We have an exciting opportunity to join our team as a Data Science Analyst/Engineer. In this role, the successful candidate Data Engineer / Data Scientist will work to build the data foundation for the groups machine learning and decision-analytic research. This role has two intertwined halves: engineering and analysis. On the engineering side, the position involves working directly with patient electronic health record (EHR) data and other patient registry datasets, including data extraction, curation, cleaning, harmonization, and pipeline development. On the analytic side, the curated data feed advanced machine learning and deep learning models, which are integrated into multimodal frameworks for prediction and decision analytics. There are also strong opportunities to help incorporate imaging and transcriptomic (and other -omic) datasets into cross-cutting, cutting-edge methodologies, and to take initiative on new approaches that improve patient care.

Requirements

• Masters degree in a quantitative discipline (Biomedical Informatics, Computer Science, Machine Learning, Applied Statistics, Mathematics or similar field) and 3 years of experience in machine learning/ data science, or a Bachelor's degree with 5 years of relevant experience.
• Proficiency in at least one programming language (Python or R) and experience using machine learning libraries and tools (e.g., scikit-learn or equivalent R packages)
• 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 software engineering principles. Experience in integrating modern software architectures.
• Knowledge and some experience in operational aspects of software 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

Nice To Haves

• PhD degree in a quantitative field (Biomedical Informatics, Computer Science, Machine Learning, Applied Statistics, Mathematics or similar field) + 2 years experience.
• Two years of hands-on experience managing and analyzing large electronic health record (EHR) and other patient registry datasets.
• Demonstrated skills in design and implementation of complex machine learning models.
• Demonstrated knowledge of software engineering and operational skills through prior projects.
• Demonstrated ability to work effectively with large, complex healthcare datasets in support of clinical, operational, or research initiatives.
• Experience applying machine learning methods to real-world healthcare data and translating findings into actionable insights.
• Experience collaborating with multidisciplinary teams, including clinicians, researchers, and operational leaders.
• Experience with deep learning methods or frameworks is preferred.

Responsibilities

• Data engineering and curation: extract, curate, clean, harmonize, and manage large EHR and other patient registry datasets, and build reliable, reproducible data pipelines.
• Machine learning and deep learning: develop, train, and evaluate advanced machine learning and deep learning models on curated patient data.
• Multimodal integration: integrate diverse data types into multimodal models for prediction and decision analytics, with opportunities to incorporate imaging and transcriptomic datasets.
• Methodological innovation: contribute to and help drive cross-cutting, cutting-edge methodologies and initiatives aimed at improving patient care.
• Communication and collaboration: write clearly, present results effectively, and work closely with a multidisciplinary team of physicians, statisticians, data scientists, and researchers.

Benefits

• financial security benefits
• a generous time-off program
• employee resources groups for peer support
• holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care.

What This Job Offers

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