Data Science Engineer: EHR & Multimodal ML Architect

NYU Grossman School of Medicine; New York (NY); On-site; USD 85,000 - 127,000; Full time

Job summary

NYU Grossman School of Medicine in New York seeks a Data Science Analyst/Engineer to build the data foundation for machine learning and decision-analytic research. The role combines data engineering with applied analytics on EHR and patient registry datasets.

You will develop scalable data pipelines, train and evaluate ML models, and explore multimodal integration with imaging or -omics data to improve patient care.

Qualifications

• Master's degree in a quantitative discipline (Biomedical Informatics, CS, ML, Stats, Math) and 3 years ML/DS experience.
• Bachelor's degree with 5 years relevant experience in ML/DS.
• Proficiency in Python or R and ML libraries (scikit-learn or equivalent).
• Knowledge of predictive modeling, design, development, evaluation, deployment, and scaling to large datasets.

Responsibilities

• Data engineering and curation: extract, curate, clean, harmonize, and manage large EHR datasets and build reliable data pipelines.
• Machine learning and deep learning: develop, train, and evaluate advanced models on curated data.
• Multimodal integration: integrate diverse data types into models for prediction and analytics, with imaging/-omics opportunities.
• Methodological innovation: contribute to cross-cutting, cutting-edge methodologies to improve patient care.
• Communication and collaboration: present results and work with physicians, statisticians, data scientists, and researchers.

Skills

Python

R

Machine Learning

Data Science

SQL

NoSQL MongoDB

Hadoop/MapReduce

Spark

Docker/Containerization

Software Engineering

Education

Master's degree in quantitative field

PhD degree in quantitative field

Bachelor's degree with 5 years relevant experience

Tools

Hadoop/MapReduce

Spark

MongoDB

Docker

Job description

NYU Grossman School of Medicine in New York seeks a Data Science Analyst/Engineer to build the data foundation for machine learning and decision-analytic research. The role combines data engineering with applied analytics on EHR and patient registry datasets.

You will develop scalable data pipelines, train and evaluate ML models, and explore multimodal integration with imaging or -omics data to improve patient care.