Senior Computational Biologist/ Data Scientist

Published date Posted on Indeed on May 10, 2022 (17 d ago)

Are you passionate about computational biology and bringing treatments to patients faster?

Pathos (www.pathos.com) is a venture-backed AI-enabled therapeutics company focused on revolutionizing the R&D process and bringing drugs to market at an unparalleled pace.

As a core focus, Pathos leverages one of the largest real-world multi-modal datasets in oncology to take a data-centric approach to identify known and novel targets and validate those targets with iterative trial designs. We believe that with the right data, computational approaches, and drug development expertise, we can accelerate drug discovery, trial design, and clinical development to advance breakthrough therapies for patients.

As a senior computational biologist at Pathos, you would work alongside a multi-disciplinary team to prioritize drug candidates, match treatments to defined patient populations, and discover new clinically actionable patient populations. The ideal candidate has demonstrated creativity in the application of computational methods to answer oncology research questions. They are passionate about oncology research and excited to help shape the direction of a new team.

Responsibilities:

  • Independently develop and enhance workflows to analyze large, complex patient clinical and molecular datasets
  • Test hypotheses, interpret results, and make recommendations
  • Act as a subject matter expert within the larger team
  • Present and communicate findings internally and externally to diverse audiences

Qualifications:

  • Background in computational research with a PhD or MS in a field such as bioengineering, bioinformatics, computational biology, physics, or molecular biology; Ideally, previous experience in the biotech/pharmaceutical industry
  • Fluent in R (or the ability to transition to R/python)
  • Oncology research experience and knowledge of public databases and tools is preferred
  • Experience deriving insights from high-dimensional omics datasets (e.g., RNAseq, WES/WGS, proteomics, single-cell genomics); Ideally, exposure to patient clinical trial data or real-world data
  • Proficiency in the application of statistics and machine learning methods; Experience choosing and applying methods to real datasets
  • US work authorization

This position is remote.

Job Type: Full-time

Pay: $120,000.00 - $180,000.00 per year

Benefits:

  • Dental insurance
  • Flexible schedule
  • Health insurance
  • Health savings account
  • Life insurance
  • Paid time off
  • Parental leave
  • Vision insurance

Schedule:

  • Monday to Friday

Education:

  • Master's (Required)

Work Location: Remote


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