Lead Physician Informaticist - Windreich Department of AI & Human Health Research
The Mount Sinai Health System (MSHS) is one of the largest healthcare systems in the United States and is at the forefront of leveraging clinical excellence and cutting-edge technology to advance patient care, research, and innovation through data-driven insights. MSHS is home to Minerva, the world’s fastest supercomputer based in an academic medical center, and the Artificial Intelligence Ready Mount Sinai (AIR·MS) research platform. Both are part of a computational and data ecosystem that includes cohort query tools, AI agents, and thousands of applications. Several multi-modal data sources, such as electronic health record (EHR) data from our system-wide Epic instance, and millions of digital pathology slides are linked together and available for analytics, research, and quality improvement initiatives. AIR·MS serves as a key entry point and infrastructure for dozens of departments, groups, and institutes throughout MSHS.
We are seeking an engaged physician informaticist with expertise in computation, data analytics, AI, and U.S. healthcare data. The Lead Physician Informaticist partners with researchers and clinicians to ensure effective use of AIR·MS and the broader data ecosystem. In this collaborative, clinically driven role, you will bridge clinical, operational, and research needs across MSHS. Responsibilities include engaging with stakeholders to understand needs, identifying barriers, developing roadmaps, and supporting the deployment of new AIR·MS capabilities. You will also help translate complex research questions into actionable data queries and develop Python/R scripts to generate insights from the OMOP CDM warehouse.
- Leads researcher and clinician engagement, including needs assessment, communication planning, roadmap development, and user experience optimization.
- Partners 1:1 with clinicians, researchers, and analysts to refine questions and deliver tailored data solutions.
- Communicates complex data concepts clearly across varying levels of expertise.
- Designs, writes, and optimizes SQL queries and Python/R scripts against the OMOP CDM to extract and analyze clinical, revenue and research data.
- Educates, trains and mentors users on EHR data structures, OMOP CDM concepts, data limitations, cohort definition, cohort query tools, analytical tools and best practices for self-service analytics.
- Helps to support researchers to address various challenges associated with data use and analysis across the translational spectrum (T0 to T4).
- Oversees a user ticketing system and develops training sessions on health care data and data warehouses including the use of query tools and direct SQL.
- Validates data outputs for accuracy, completeness, and appropriateness.
- Identifies and communicates potential biases or limitations in EHR-derived data.
- Collaborates with technical, clinical, and compliance teams to improve functionality, data quality, and governance.
- Ensures compliance with regulations, institutional policies, and ethical standards in all data handling and dissemination.
- Contributes to documentation, standard query libraries, and training materials to enhance organizational data literacy.
- Has familiarity with modern artificial intelligence and machine-learning methodologies, including the use of supervised and unsupervised methods, large language models, and transformers.
- May manage a small number of staff as required.
- Bachelors degree in a technical discipline; Masters degree preferred
- 12-15 years preferred of related experience, including 8 years of demonstrated ability in technology area. In-depth knowledge of associated technology areas that could impact area of responsibility; healthcare technology experience preferred
Advanced degree: MD/DO with Board Certification in Clinical Informatics strongly preferred; RN with experience in Clinical Informatics strongly preferred; PhD in a relevant field (e.g., Health Informatics, Bioinformatics, Epidemiology, Biomedical Informatics, or Computer Science with health focus) will be considered for exceptional candidates.
Preferred:
- At least seven years of experience in clinical informatics at a healthcare system and/or in biomedical research.
- Understands and has expertise in a broad spectrum of clinical data types, transformations, concept mappings, and standards (such as OMOP Common Data Model, SNOMED, ICD, RxNorm, LOINC, and ontologies) used at academic medical centers.
- Demonstrated proficiency in SQL (including complex joins, stored procedures, window functions, and performance optimization) with experience querying large healthcare datasets, as well as using Python and R programming languages.
- Understands how to perform quality assurance and quality control assessments of queries, data, and data warehouses.
- Must have experience with HIPAA, Compliance and Cybersecurity requirements.
- Strong understanding of EHR data, including clinical workflows, documentation practices, and common data quality issues in EHR derived data.
- Familiarity with Epic Clarity and Caboodle data models is preferred.
- Experience preferred with a variety of multi-modal data including but not limited to: Radiology DICOM tags, Pathology metadata, genomic/WES, return of genetic results.
- Understands best practices for software development lifecycles.
- Experience working with students, residents, fellows, staff, faculty, administrators with different levels of technological and medical expertise in a large academic medical system.
- Effective communication and collaboration skills.