Manager, Clinical Informatics

Role Summary

Manager, Clinical Informatics at Regeneron Genetics Center. You will organize, analyze and interpret health information aggregated from electronic health records, surveys, digital devices, and laboratory assays from multiple collaborators. You will develop and implement standards for health data, code repositories, pipelines and analysis tools to facilitate interacting with data, and participate in downstream analysis using machine learning, genomics, and epidemiology.

Responsibilities

• Developing and maintaining a toolkit with key functions, APIs, and summaries that help users understand, interpret, and interact with phenotype data. Knowledge of Python, and ideally R, SQL and/or C++.
• Developing tools and code to transform diverse health data into a harmonized format compatible with analytical tools and processes, primarily using Python and data science libraries.
• Reviewing the structure, content, and quality of phenotype data from multiple sources, coordinating with stakeholders.
• Discussing challenges and opportunities of using health data to characterize human health and disease; epidemiology methods experience is a plus.
• Working with cloud environments and platforms, particularly AWS, to run analysis and data processing at scale and automate key processes.
• Presenting results and summaries to diverse technical audiences, requiring strong communication skills.
• Collaborating in a highly interactive team environment to maintain motivation and performance.

Qualifications

• Required: PhD (or MS with additional years in lieu) in Computer Science, Health Informatics, Clinical Informatics, Biostatistics, or related field; at least 3 years of experience organizing large datasets in a research setting.
• Preferred: Demonstrated knowledge of Python and key data science libraries; knowledge of R, SQL and/or C/C++; experience mapping data to ontologies (ICD-10, RxNORM, LOINC); data quality control, summarization and visualization.

Skills

• Python and data science libraries; R, SQL, or C/C++ advantageous
• Data transformation and harmonization
• Data quality assessment and visualization
• Effective communication and ability to present to diverse audiences
• Team collaboration in a fast-paced environment

Education

• PhD in Computer Science, Health Informatics, Clinical Informatics, Biostatistics, or related field (or MS with additional years of experience)

Additional Requirements

• Experience with cloud platforms (AWS) and scalable data processing