Associate Manager, Statistical Genetics and Machine Learning

Regeneron Pharmaceuticals • Tarrytown, NY

90d • $126,700 - $206,900

About The Position

We are seeking a talented scientist to join the Statistical and Machine Learning team at the Regeneron Genetic Center (RGC). The mission of the team is to develop new methods and implement pipelines that extract the most value from large scale sequenced and deeply phenotyped individuals in order to make new drug target discoveries and support existing targets. The Regeneron Genetics Center houses one of the world's largest and most complete datasets on human genetics in the world. This is a fantastic opportunity to join an inspiring and talented team that is at the forefront of statistical genetics and machine learning for drug discovery and translational genetics. The rapid growth in sequencing datasets at the RGC comes with many new challenges from a methods perspective. The scale at which analysis is carried out necessitates we provide state-of-the-art methods that are computational efficient, statistically powerful, robust and flexible. In addition, the complexity and depth of our phenotype data is increasing, and we increasingly have available imaging on our sequenced subjects. Your role will be to develop new methods, test existing methods and implement user friendly pipelines that extend the analytical tool kit of the RGC. You will work together with the inclusive and multidisciplinary teams and colleagues at the RGC and Regeneron to support findings into new biological insights.

Requirements

• A PhD in Statistical Genetics, Machine Learning, Imaging Analysis, Human (Population) Genetics, Genetic Epidemiology, Computer Science, Computational Biology or a related field. Postdoc experience is also desirable.
• Expertise in developing software and/or pipelines with programming language like Python or C++.
• 2+ years of experience with tools and analysis for carrying out genetic association studies and/or analysis of large scale datasets and/or imaging datasets.
• Experience with standard toolkits including PyTorch, JAX, TensorFlow, Keras, ScikitLearn.

Nice To Haves

• Demonstrable experience with a variety of methods and tools from the fields of statistical genetics or statistical machine learning.
• A clear understanding of the methodological aspects and approaches involved in GWAS and ExWAS.
• Experience with setting up a codebase for human genetic studies in a high-performance computing environment.
• An interest or experience in working with imaging data.
• Experience building and executing pipelines on an HPC or cloud infrastructure.

Responsibilities

• Develop new statistical and machine learning approaches, data processing pipelines and establish internal data practices that can be applied to datasets with millions of sequenced samples.
• Work closely with the imaging ML team to extract phenotypes from medical images, involving direct machine learning projects with images or downstream analysis of derived phenotypes in GWAS and ExWAS studies.
• Collaborate with other groups in the RGC to develop user friendly pipelines and support users in applying methods in ongoing studies.
• Trial blue sky ideas.
• Generate, summarize and present results in internal and external meetings to a variety of audiences.
• Deliver reliable analyses across projects in a dynamic, high-pace and creative working environment.
• Lead and contribute to the writing of scientific reports and publications.

Benefits

• Health and wellness programs
• Fitness centers
• Equity awards
• Annual bonuses
• Paid time off for eligible employees at all levels

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Industry: Chemical Manufacturing
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees