Data Analyst II - Windreich Department of AI & Human Health Research

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).

The Data Analyst II oversees activities related to data integrity, security and enhancement of the value of data. The Data Analyst II may direct the movement of data across multiple systems; oversee its validation and organization and make sure that data is available to appropriate people and systems within an organization. The Data Analyst II will also develop and execute reports that will be important assets of the practice as they continue to develop and evaluate a new model of care.

This position will be in the lab of Dr. Lili Chan housed in the Department of Artificial Intelligence and Human Health at the Icahn School of Medicine at Mount Sinai in Manhattan, New York, NY, USA.

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. 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 the Mount Sinai Data Warehouse (b) The BioMe Biobank Program with >30,000 patients with whole exome sequencing data linked to longitudinal clinical data. The candidates will have the opportunity to develop their own research projects and to lead or participate in local as well as international collaborations.

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 patients’ lives in a clinical setting.

• Work with the clinical and administrative staff of the practice to define data reporting needs
• Develop analytic reports that are easily understandable by clinical and administrative staff.
• Use modeling techniques and tools in analyzing and specifying data structure
• Implement best practices in data management to ensure the integrity of the data, the quality of data processes and deliver analyzable or analyzed data to a variety of internal and external clients of the affiliated practice
• Maintain data integrity and completes data analysis as necessary
• Complete data capture, data extraction and analysis
• Develop, maintain or implement procedures for data entry, data cleaning, documentation and other administrative tasks
• Document, implement, maintain or recommend operating methods to improve processing, distribution, data flow, collection, database editing procedures
• May define parameters for file or space utilization
• Work closely with IT management and staff
• Access data in the Data Warehouse, as required
• Assist clinical and administrative staff with queries, statistical analyses, reports and technical difficulties related to data retrieval
• Design and write custom applications needed to ensure the database meets requirements for the entry, management and reporting of data
• Identify and recommend solutions to data management issues
• Maintain knowledge of the current regulations and technologies related to data management
• Write and prepare manuscripts and other materials for internal and external audiences
• Perform other related duties
• Help to build and perpetuate a practice environment and culture of collaboration, respect, learning, flexibility and fun among all team members
• Bachelors degree in computer science, statistics and/or related field required, or combination of equivalent work experience and education. Masters degree in relevant field of study preferred (e.g., biomedical informatics, clinical informatics, statistics, epidemiology, computer science, etc.).
• 3+ years of analytics experience including report development and database application/management experience, preferably in a large medical center or healthcare environment

Preferred

• Significant experience in large language models (LLMs), natural language processing (NLP), and machine learning is preferred, ideally demonstrated through published research and/or publicly available code. Expertise in developing, fine-tuning, evaluating, and deploying LLMs is preferred, including experience with modern deep learning frameworks and LLM tooling (e.g., PyTorch, Hugging Face Transformers, TensorFlow) and techniques such as prompt engineering, retrieval-augmented generation (RAG), and model evaluation.
• Expertise with programming and statistical software experience in R and/or Python.
• Formal computer science, statistics, or epidemiological training is a strong advantage.
• Familiarity with the publication process.