Data Scientist, Drug Discovery

Palo Alto, California
Feb 23, 2018
Required Education
Position Type
Full time

Auransa Inc., formerly known as Capella Biosciences, is an AI-driven pharmaceutical startup focusing on developing precise medicines for cancer, aging, and other disorders.  We are a group of veteran drug developers, data scientists, chemists, and more, who share the common purpose of developing treatments for serious human diseases in order to save lives and relieve suffering.  

We are looking to add a self-motivated and innovative data scientist to our team. This person will help drive the development and improvement of our state-of-the-art AI drug discovery engine through methods and algorithm innovation. The position requires close collaboration with the pre-clinical and biology teams to develop novel compounds, discover biomarkers and identify mechanisms of action. The successful candidate has a history of getting things done both independently and in a team within a fast-paced environment, and will have an exciting opportunity to make a direct impact on the company’s drug discovery pipeline.

Required Qualifications

  • PhD in computational biology, bioinformatics, biostatistics, computer science, or closely related quantitative discipline
  • At least 2 years of experience in applying statistics, machine learning and analytics techniques to real-world data for decision support
  • Experience using Python and/or R for scientific analysis and methods development
  • Ability to communicate analytics results to people from a range of technical and non-technical backgrounds
  • Strong publication record in the area of algorithm development

Preferred Qualifications

  • Experience conducting analysis of biological data generated from multiple ‘omics platforms
  • Practical domain exposure to one or more of the following: oncology, genetics, systems biology, immunology, oncology, infectious disease, PK/PD or medicinal chemistry.
  • Work experience in the biotech or pharmaceutical industry.
  • Experience in applying deep learning to practical problems in the industry

Depending on relevant years of experience and background, we will also consider the candidate for a leadership role.

Please submit your cover letter and CV