The Data Analyst I is responsible for implementing best information technology data management practices in an effort to improve and ensure quality, streamline data cleaning efforts and deliver analyzable databases within agreed upon project timelines.
We are inviting applications for a Data Analyst position in data science and machine learning with a specific interest in applications to clinical data, including electronic health records (EHR).
Key topics of interest include but are not limited to: natural language processing, large language models, predictive modeling for disease outcomes and personalized therapeutic recommendations, working with common data model EHR standards (e.g., OMOP), multi-modal (e.g., genomics, imaging, and clinical data) deep learning for clinical decision support, unsupervised learning to discover biologically-relevant disease subtypes, among others. We have an interest in many disease domains including nephrology, cardiology, radiology, psychiatry, and others.
Data and Resources:
Data resources include (a) Access to >8 million patient records in theΒ Mount Sinai Data Warehouse (b)Β The BioMe Biobank Program with >30,000 patients with whole exome sequencing data linked to longitudinal clinical data.Β The candidates will have the opportunity to develop their own research projects and to lead or participate in local as well as international collaborations.Β
The analyst will join a dynamic team of data scientists, geneticists, and clinicians and participate in unique opportunities to apply deep learning for important scientific breakthroughs and to directly impact patientsβ lives in a clinical setting.
Significant experience in biostatistics/machine learning techniques is preferred, ideally with published work and/or code available. Expertise with deep learning frameworks is preferred (e.g., TensorFlow, PyTorch, Keras). also preferred.