Associate Manager, Machine Learning and Statistical Genetics

Location
Tarrytown, NY, United States
Posted
Sep 11, 2020
Ref
20320BR
Discipline
Science/R&D, Genetics
Required Education
Doctorate/PHD/MD
Position Type
Full time
SUMMARY:

Contribute to the analysis and interpretation of 100,000s of genotyped and sequenced humans, with the goal of generating the knowledge to help Regeneron to deliver better medicines to the patients who need them.

Develop machine learning methods and solutions to a range of problems in statistical genetics, imaging genetics and analysis of electronic health records.

Work collaboratively with other specialists in genomic data analysis, biology, computation and medicine to design, execute and refine analyses that connect genetic variation to human diseases and health and help develop and implement the methods and tools that will enable these analyses to be executed and interpreted at scale.

A TYPICAL DAY MIGHT INCLUDE THE FOLLOWING:
  • Develop and apply cutting edge machine learning, image analysis and statistical genetics methods and deploy them at scale to answer biological and disease genetics questions that cover all the areas of interest of the RGC.
  • Demonstrated ability to execute and interpret analyses of genomewide association analysis, with sequencing or genotyping data as a substrate, is desirable.
  • Expertise with modern cluster and cloud computing environments is required. The candidate will routinely use sophisticated tools for machine learning (scikit learn, tensorflow), genomic analyses and computation (Python, C/C++, Javascript, R) to implement new methods and execute analyses at scale.
  • Critically review and provide feedback on analyses plans, results and summaries to ensure they are accurate and reliable. Identify potential problems and propose remedies or refinements.
  • Outstanding communication skills to present new statistical methods and concepts and the results of human genetic studies to a variety of technical audiences, ranging from specialists in genetics and computation to specialists in biology, drug design and medicine.
  • Ability to work in a highly interactive environment with a diverse team of colleagues.


THIS ROLE MIGHT BE FOR YOU IF YOU HAVE:
  • Experience of developing and applying machine learning, statistical genetics or image analysis methods at scale.
  • Experience with multiple tools for large scale genetic analyses and DNA sequence data is preferred.
  • High proficiency with one or more modern programming language (Python, C/C++, Javascript, R) and their associated packages for statistics, modeling and visualization.
  • Familiarity with Unix/Linux, shell scripting, SGE clusters, AWS environment
  • Ability to summarize and distill results concisely. Excellent oral presentation and writing skills.
  • Expertise in developing analysis packages and tools is highly desired, as demonstrated by leadership or contributor roles to statistical packages available on GitHub or elsewhere.
  • 2- 3 years minimum of experience post PhD.


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.

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