Associate Scientist, Bioinformatics, Molecular Profiling

Location
Tarrytown, NY, United States
Posted
May 02, 2019
Ref
16600BR
Required Education
Doctorate/PHD/MD
Position Type
Full time
Known for its scientific and operational excellence, Regeneron is a leading science-based biopharmaceutical company that discovers, invents, develops, manufactures, and commercializes medicines for the treatment of serious medical conditions. Regeneron commercializes medicines for eye diseases, high LDL-cholesterol, atopic dermatitis and a rare inflammatory condition and has product candidates in development in other areas of high unmet medical need, including rheumatoid arthritis, asthma, pain, cancer and infectious diseases.

Summary
Seeking a creative computational scientist to translate multiomics data into clinically relevant insights that advance our understanding of cardiovascular disease. The scientist will create and apply novel methods to interpret and integrate across diverse data types, including from cutting-edge technologies developed internally. The successful applicant will have strong computational skills, an ability to clearly communicate with wet lab scientists and clinicians, and a desire to learn relevant disease biology and contribute to charting research direction.

Responsibilities
  • Derive hypotheses from pre-clinical and clinical gene expression profiling studies for target and biomarker discovery.
  • Write algorithms to jointly analyze transcriptomic, genetic, and clinical data from patient cohorts.
  • Collaborate with scientists in the Cardiovascular, Fibrosis, and other groups at Regeneron, as well as external collaborators to design and interpret molecular profiling experiments.
  • Lead development of statistically robust tools for analyzing data from novel technologies (CITE-Seq, single-nuclei Sequencing, TCR-Seq, etc.)
  • Present results to colleagues, senior management and collaborators.
  • Contribute to automating pipelines, and to building tools and visualizations that allow researchers across the company to deep dive into molecular profiling data.
  • Introduce novel research questions to drive our research forward.

Requirements
The candidate will possess the following qualifications:

• Demonstrated academic or professional achievement in bioinformatics, statistics, data science, or similar.

• PhD strongly preferred, but exceptional Master's degree candidates also considered.

• Proficiency in programming languages such as R, python, bash.

• Excellent communication and presentation skills.

• Collaborative, result-oriented, and able to work in a multi-project and fast-paced environment.

Strongly preferred:

• Knowledge of and experience in machine learning algorithms, including predictive modeling.

• Experience in analysis of diverse data including RNA-seq, Single-cell RNA-seq, DNA-seq, ChIP-seq, and EHRs.

• Knowledge of bioinformatics tools, databases, and approaches to support drug discovery programs.

• Ability to create interactive data visualizations.

• Experience with cloud computing infrastructure.

• Familiarity with cardiovascular and fibrosis biology a plus.

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's unwavering commitment to combining good science & good business.

To all agencies: Please, no phone calls or emails to any employee of Regeneron about this opening. All resumes submitted by search firms/employment agencies to any employee at Regeneron via-email, the internet or in any form and/or method will be deemed the sole property of Regeneron, unless such search firms/employment agencies were engaged by Regeneron for this position and a valid agreement with Regeneron is in place. In the event a candidate who was submitted outside of the Regeneron agency engagement process is hired, no fee or payment of any kind will be paid.

Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability status, protected veteran status, or any other characteristic protected by law.