Senior Data Scientist

Added: 5/4/2022

REF: 22037

Contract: Permanent

Location: California, United States

Location: San Francisco, CA; Boston, MA; New York, NY (hybrid)

Join a team of data scientists building a robust computational platform for advancing the R&D of new medicines. Opportunity to work across traditional industry boundaries in a fast-paced startup environment, with a diverse array of data spanning biology, computational chemistry, imaging, electronic medical records, text notes, clinical trials, and data from our labs.

About The Role

We are looking for an experienced Senior Data Scientist to design and implement solutions to real-world small-molecule modeling problems to advance computationally accelerated drug development programs. You will apply and enhance the capabilities of our AI-based platform to advance real-world, active drug development programs. Successful candidates must be committed to working with a diverse set of scientists, entrepreneurs, and domain experts in ways that cut across traditional industry boundaries in a fast-paced startup environment.

Our AI-based platform leverages human-centric data to enable researchers to discover and develop new drugs. It is a fully integrated, AI-powered, cloud-native platform that leverages human-centric data to create new approaches to drug discovery and development enabling researchers to minimize the cost and time associated with discovery, development, and delivery of novel therapeutics. The predictive insights produced by our AI platform rely on high-quality, high-density human-centric data that is sourced from multiple data sets, processed both remotely and on site through a highly complex process.

Day to Day

  • Work with data scientists, researchers, product teams, and other domain experts to build solutions to complex data-oriented problems.
  • Train, assess, deploy, and interpret statistical machine learning models that inform and advance our programs.
  • Design, develop, and scale data curation and modeling pipelines for our large-scale, high-throughput applications.

Requirements

  • A PhD (or Master’s with experience) in Computational Chemistry, Computational Biology, Bioinformatics, or related quantitative fields
  • Direct experience or exposure to the drug discovery process, with an understanding of how computational methods deliver impact on preclinical discovery (target identification & validation; small molecule development; elucidating molecular mechanisms of action and modifiers of effects)
  • Experience with modern statistical analysis and machine learning techniques, particularly in the context of large-scale, high-throughput dataset analysis.
  • Strong familiarity with the various tools and environments for successful, modern data science: beyond a fundamental comfort zone with the shell, Python/R, and other scripting languages, you have experience using HPC/grid/cloud computing environments, programming against API services, accessing data from a heterogeneous mixture of flatfiles, SQL relational databases, noSQL/JSON object storage, and/or RDF/OWL triple-stores.
  • Strong analytical, problem-solving, and communication skills, including facility with Rmarkdown and/or Jupyter Notebooks for communicating reproducible results; and the ability to also condense, summarize, and synthesize those results into informative and actionable presentations to less technical audiences.
  • Strong personal project management skills with significant practical experience managing your time split between multiple, parallel projects; experience with Agile processes and frameworks for team collaboration (e.g. Kanban, Atlassian tools)

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