Data Science Analyst/Engineer
$84,578–$126,992 year
On-siteNew York, United States
EXPIREDNew York, United StatesOn-siteFull Time$84,578–$126,992 yearMasters DegreeEnterprise
Full TimeMasters DegreeEnterprise
Job Summary
Extract, curate, clean, and harmonize large electronic health record and patient registry datasets while building reliable, reproducible data pipelines. Develop, train, and evaluate advanced machine learning and deep learning models on curated patient data, integrating diverse data types into multimodal frameworks for prediction and decision analytics. Contribute to cross-cutting methodologies that incorporate imaging and transcriptomic datasets to improve patient care. Collaborate with a multidisciplinary team of physicians, statisticians, and researchers to present results effectively and drive innovation.
Required Qualifications
- Masters degree in a quantitative discipline (Biomedical Informatics, Computer Science, Machine Learning, Applied Statistics, Mathematics or similar field)
- 3 years of experience in machine learning/ data science
- Bachelor's degree with 5 years of relevant experience
- Proficiency in at least one programming language (Python or R)
- 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 and some experience in clinical and operational aspects of healthcare delivery
- Excellent written and oral communication skills for a variety of audiences
- Must be able to effectively communicate with all levels of the organization
Desired Qualifications
- 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
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