Staff Scientist/Manager, Clinical Informatics | GenomeWeb

Staff Scientist/Manager, Clinical Informatics

Regeneron Pharmaceuticals
Job Location
Tarrytown, NY
Job Description

The position will be responsible for conducting analyses involving clinical and phenotypic data for genetics studies as well as clinical development and commercial programs. Responsibilities will include curating, cleaning, and analyzing large-scale phenotypic datasets, including de-identified EMR extracts from external collaborators, targeted clinical datasets in selected cohorts, and internal datasets from clinical trials and other human subject research. The position will involve working within a team of database administrators, biostatisticians, clinical scientists, and programmers to structure and mine clinical and phenotypic data sets and support genomic studies and association analyses. The position will require coordination and collaboration with other scientists within the department, research and clinical scientists at Regeneron, and external collaborators.

Additional responsibilities include, but are not limited to:
- Work within a team of programmers, database administrators, statisticians, and clinical scientists, as well as external collaborators and facilitate EMR data extraction, transformation and processing from multiple health system partners.
- Conduct data analysis, including mining and curating of phenotypic datasets with primary responsibility in developing and identifying clinical phenotypes and cohorts of interest for “phenotype first” genomic analysis of associated samples and efficient data mining and association analysis in both phenotype first and genotype first queries.
- Conduct algorithm development, development of data models, natural language processing (NLP) and textual mining of “scrubbed” and de-identified healthcare provider notes.
- Implement GUIs and GUXs such as i2b2, tranSMART, or other software to enable a scalable data warehousing and informatics framework and data mining/querying by department team members and broader Regeneron scientists.
- Close collaboration and coordination with external health system collaborators and bioinformatics teams mining EMR and phenotypic data sets. Work with these collaborators to structure data and develop algorithms, rules engines, and querying tools to access and curate the phenotypic datasets.
- Develop analytic methodologies and approaches to address queries for cohort selection related to sequencing and epidemiological outcomes studies. Execute the analyses in a timely, accurate and reliable manner. Communicate findings clearly to diverse stakeholders and document work for training and replication purposes.
- Utilize multiple sophisticated Analytic Methodologies and Data Reporting/Management tools, and contribute to work presented to senior leadership and externally to collaborators.
- Implement and use Analytic Methodologies and Data Reporting/Management Tools (e.g. SQL Query Analyzer, Crystal Enterprise).
- Function as a "super user" of either priority Analytic Methodologies or Data Reporting/Management tools.


This position requires a PhD or Master's degree in Statistics, Computer Science, Information Science, or other relevant analytical/data field, and a minimum of three years of reporting and/or data analysis experience. Healthcare and EMR data analytics experience are also required. Additional requirements include:
- Familiarity with data mining, clinical databases, hospital health informatics databases including EPIC and EMR (electronic medical records) data structures.
- Familiarity with clinical data standards, database architecture and administration, as well as SQL programming.
- Experience with HIPAA and experience with IRB protocols around use of use of EMR data.
- Experience working with genomic and bioinformatics investigators.
- Involvement in relevant programs such as eMERGE, HMO Research Network, or other such projects is preferred.
- Proficiency with user interfaces such as i2b2 and tranSMART.
- Demonstrates proficiency with quantitative Analytic Methodologies and Data Reporting/Management Tools.
- Demonstrates competence in Data Reporting/Management Tools (e.g. SQL Query Analyzer, Crystal Enterprise).
- Demonstrates understanding of relational database concepts and query tools.
- Demonstrates strong analytical and advanced microcomputer skills.
- Demonstrates the ability to multitask and manage simultaneous projects to meet deadlines with a strong attention to detail.
- Demonstrates ability to interpret and communicate analytical information in a clear, concise manner.

This is an opportunity to join our select team that is already leading the way in the Pharmaceutical/Biotech industry. Apply today and learn more about Regeneron Genetics Center’s unwavering commitment to combining good science & good business.

How to Apply

Please apply online at or send your resume directly to Lindsay Vail at

About Our Organization

The Regeneron Genetics Center is a wholly-owned subsidiary of the Company organized to collaborate with health systems and research groups to elucidate, on a large scale, genetic factors that cause or influence a range of human diseases. Building upon Regeneron's strengths in mouse genetics and genetics-driven drug discovery and development, the Center will specialize in ultra-high-throughput exome sequencing and computational biology; discovery of genotype-phenotype associations through linkage to well-annotated de-identified patient electronic medical records; and validation of discoveries using Regeneron’s VelociGene® technology. Our interests encompass a breadth of different areas such as Mendelian and family frameworks, large-scale population genetics (both common and rare variants), and gene-gene interactions. Program goals include target discovery, indication discovery, and patient-disease stratification. Objectives include advancing basic science around the world through public sharing of discoveries, providing clinically-valuable insights to physicians and patients of collaborating health-care systems, and identifying novel targets for drug development.

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