Precision Medicine-Quantitative Translational Scientist

Location
Tarrytown, NY, United States
Posted
May 29, 2021
Ref
25024BR
Required Education
Doctorate/PHD/MD
Position Type
Full time
The Quantitative Translational Scientist (QTS) leads precision medicine initiatives to inform clinical studies through analytical, computational and novel scientific/technological strategies. The scientist supports clinical and clinical experimental science programs by overseeing and performing exploratory analysis of genomic, transcriptomic, proteomic, metabolomic, EHR and other biomarker and exploratory endpoints (including data collected from wearables and endpoints derived from imaging analyses). The scientist also leads the development of scientific software for querying, visualizing, analyzing and interpreting data to advance the capabilities of the Precision Medicine department to answer scientific questions through computational means. She/he cross-functionally leads projects with many internal stakeholders (biostatisticians, bioinformaticians, epidemiologists, mathematicians, clinical and research scientists) and external collaborators for the quantitative needs of Precision Medicine. She/he works collaboratively with scientists and vendors to assure that exploratory statistical and bioinformatics analyses of biomarker data are performed correctly. The scientist keeps abreast of the scientific literature, new technologies and industry trends related to precision medicine, genomics and bioinformatics to identify novel strategies to advance drug development.

A day in the life may include the following:
  • Collaborate with bioinformatics, biostatistics, pharmacometrics, clinical outcomes innovation labs, and imaging, to develop specific methodology to analyze data of all types, including but not limited to, transcriptome, proteome, metabolome, and other biomarker and exploratory endpoints (including data collected from wearables and endpoints derived from imaging analyses).
  • Plan and execute (or oversee implementation) of exploratory and biomarker-based endpoint measurements in clinical studies (including natural history studies on human subjects). Specifically coordinate, and oversee the preparation, execution, reporting, and documentation of exploratory analysis projects.
  • Collaborate with lead projects data scientists, Molecular Profiling, Regeneron Genetics Center (RGC), Clinical Outcomes Innovation Labs, and other groups in the design and interpretation of various biomarker studies (genetics, gene expression, methylation analyses, eQTL, etc), digital health-care analytics (wearables), and any other exploratory analyses initiated or conducted by the Precision Medicine/Early Clinical Development department.
  • Integrate internal and external complex datasets to perform bioinformatics and statistical analysis on exploratory biomarker data and endpoints, providing support across a range of Precision Medicine and biomarker studies (including transcriptome, proteins and other biomarkers collected from clinical programs).
  • Ability to lead matrix teams and manage multiple projects simultaneously to deliver high quality results in a time sensitive environment. Be comfortable working with unstructured and complex datasets in unfamiliar formats to rapidly identify major clinical takeaways and turn results into complete analyses and presentations to wide audiences.
  • Communicate results and findings to key internal stakeholders and external collaborators. Specifically, contribute to the preparation of scientific presentations, manuscripts and reports, including the preparation of tables and graphs depicting biomarker research results.
  • Guide and/or create user tools for easy access of internal and external results by scientists.
In order to be considered for this position, we seek the following:
  • Ph.D with a degree in Bioinformatics, Epidemiology, Human Genetics, Statistical Genetics, Biostatistics, Statistics, Computer Science, or Physics
  • Candidate must possess theoretical understanding of translational quantitation. The candidate should have sound knowledge of statistical methodology; ability to critique devised hypotheses and results interpretation.
  • Must be able to code in C/C++, java, python, and/or R and have demonstrated experience with feature selection-based machine learning techniques
  • Familiarity with non-parametric methods, knowledge of Bayesian analytic approaches a plus
  • Should be comfortable in a Linux environment.
  • Background in biology preferred but must have at minimum a deep familiarity with biological concepts.
  • Experience in project management with minimal supervision. Demonstrate ability to effectively organize and manage multiple assignments with challenging timelines across multiple personnel.
  • Self-directed and comfortable working in teams with the ability to work and operate independently within a tight deadline environment. High degree of creativity, latitude and attention to detail required
  • Ability to be agile and flexible in daily routines
Does this sound like you? Apply now to take your first steps toward living the Regeneron Way! We have an inclusive and diverse culture that provides amazing benefits including health and wellness programs, fitness centers and stock for employees at all levels!
Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion or belief (or lack thereof), sex, nationality, national or ethnic origin, civil status, age, citizenship status, membership of the Traveler community, sexual orientation, disability, genetic information, familial status, marital or registered civil partnership status, pregnancy or maternity status, gender identity, gender reassignment, military or veteran status, or any other protected characteristic in accordance with applicable laws and regulations. We will ensure that individuals with disabilities are provided reasonable accommodations to participate in the job application process. Please contact us to discuss any accommodations you think you may need. #LI-SC1