Senior Data Scientist, Pharmacology, Quantitative Biosciences

Merck & Co.-posted 3 months ago
$126,500 - $199,100/Yr
Full-time • Senior
Onsite • West Point, PA
Chemical Manufacturing
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At our company, we are committed to improving the health and well-being of people around the world. As a leading global pharmaceutical company, we strive to make a difference through innovative research, discovery, and development of life-saving medications and vaccines. With over a century of experience and a steadfast dedication to scientific excellence, we have become a trusted name in the industry. Join our team and be a part of our mission to create a healthier future for all. We have an exciting opportunity for a Senior Data Scientist with a background in machine learning, statistics, data science to join our Pharmacology team in our West Point, PA site. In this role, you will be working collaboratively with our local discovery teams and other AIML & data science functions to advance therapeutic programs in Immunology, Neuroscience and Infectious Diseases/Vaccines, and to build computational pipelines that make better use of the data we generate.

  • Work with department pharmacologists to design statistically sound experiments and critically analyze and interpret the data from these experiments to ensure the success of discovery programs in Immunology, Neuroscience and Infectious Diseases/Vaccines.
  • Help develop novel data pipelines that move, integrate and analyze diverse sources of biological data that aid in the identification of targets, profiling of therapeutic candidates or improving the chances of translation.
  • Identify, develop and implement data visualization approaches that help drive decision making on program teams and manage resources for the department.
  • Help wrangle and analyze unstructured and structured data that will drive new translational strategies for the company.
  • Participate in the development and implementation of active learning-based approaches to drug discovery.
  • Work with automation engineers and laboratory scientists to develop the infrastructure to collect and move data off of lab-based instrumentation to help facilitate downstream analyses including those implementing AIML methodologies.
  • Identify, validate, and integrate new technologies or methodologies to increase efficiency and productivity, drive program progression, and facilitate clinical translation of discovery programs.
  • Collaborate across the network to help guide the data transformation process and build data science infrastructure.
  • Effectively communicate data analyses and computational strategies to stakeholders and management.
  • Democratize computational approaches and upskill lab-based scientists to become more data science savvy.
  • Ph.D. in Biology, Pharmacology, Data Science, Biostatistics, Computational Biology/Chemistry or other related life sciences field; or a Master's degree in the same field with 3+ years' experience in some aspect of computational drug discovery or machine learning in a pharma or biotech setting.
  • An understanding of pharmacology experiments for the purposes of drug discovery, and how to design statistically sound experiments that will help drive pipeline decisions.
  • A background in statistics and machine learning.
  • Experience with databases, database queries, scripting, programming and/or the use of statistics or analysis software including SQL, Prism, Python or R.
  • An ability to wrangle structured and unstructured data for use in downstream data analyses.
  • Experience with multiple data modalities, e.g. genomics data and/or chemical structure data, and insights on how to integrate them with other data formats and perform interpretations.
  • A robust understanding of drug discovery and clinical development and experience on drug discovery programs from at least lead identification through to the delivery of a preclinical candidate.
  • The ability to communicate effectively with and relate to a broad range of stakeholders, including senior leaders, peers, direct reports, partner organizations and external collaborators.
  • Excellent written and oral communication skills.
  • The ability to adapt to changing priorities.
  • A passion for innovation and problem-solving.
  • Experience working directly with experimentalists to design and interpret experiments.
  • A background in both experimental and computational lab work.
  • Medical, dental, vision healthcare and other insurance benefits (for employee and family)
  • Retirement benefits, including 401(k)
  • Paid holidays
  • Vacation
  • Compassionate and sick days
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