Senior Data Scientist

About the job

Position Summary

The Senior Data Scientist on the Software Solutions team will be responsible for supporting successful biopharma customer use of the REFS software platform.  This individual will be an internal expert on the capabilities of our Bayesian inference platform, with the ability to translate customer use requests into practical solutions using REFS-based analytics. The role will be responsible for providing advanced technical and scientific support for licensed clients on precision medicine applications of REFS.

Responsibilities will include training client users in the use of REFS Software, assisting client users in scientific problem formulation, data assessment, and model design, partnering with client users on the interpretation and value of scientific results generated by the REFS platform and participation in development of support materials around REFS scientific and technical applications.

Responsibilities

  • Facilitate the delivery of scientific insights to clients using REFS software and services, including onboarding, training, and providing regular technical and scientific support to users.
  • Provide feedback to GNS R&D, product, and engineering teams on the REFS software roadmap and opportunities to deliver client value
  • Identify and mitigate risks that could inhibit client success
  • In-depth understanding of the application of REFS for precision medicine, biomarker discovery, and patient stratification use cases.
  • Scientific rigor and creativity in addressing client business needs
  • Assist clients in assessment of healthcare datasets (e.g. clinical trials, omics, claims, EHR datasets) for REFS modeling
  • Support modeling workflows and model interpretation by license clients
  • Troubleshoot with clients to assist them in tailoring the REFS platform to their needs
  • Provide training to internal and external customers on the REFS platform
  • Support pre-sales and business development activities as needed

Requirements

  • Master’s Degree in Bioinformatics, (Bio)Statistics, Data Science, Systems Biology, (Bio)Physics, Mathematics, or Computer Science; PhD preferred
  • 2-5 years of relevant work experience
  • Experience in machine learning and probability theory; experience in Bayesian analysis or causal inference methods is a strong plus
  • Experience handling and manipulating large data sets
  • Proficiency in at least one statistical programming or numerical computing language; experience with R preferred
  • Familiarity with AWS and Linux systems
  • Strong written and verbal communication; a clear ability to communicate technical material to non-technical audiences simply and clearly
  • Experience working in an interdisciplinary environment is a plus
  • Passion to learn new things and solve problems

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