Principal Scientist, Discovery Data Science

2 weeks ago


La Jolla, California, United States Johnson & Johnson Full time
Job Title: Principal Scientist, Discovery Data Science

Johnson & Johnson Innovative Medicine is seeking a highly skilled Principal Scientist, Discovery Data Science to contribute to the development of innovative data science solutions for drug discovery. The successful candidate will be responsible for inventing, internalizing, and applying creative yet scientifically sound data science solutions to virtually assess molecules in the broadest possible sense.

Key Responsibilities:
  • Contribute to developing data science applications with a focus on antibodies and targeted protein degradation discovery across different therapeutic areas and projects.
  • Bridge between experimental and groundbreaking digital technologies, expertise in machine learning and artificial intelligence (AI) as applied to drug discovery.
  • Interact in a team environment built on trust and collegiality.
  • Communicate effectively and encourage colleagues to do so.
  • Evaluate and make recommendations regarding the internalization, conceptualization and development of building of innovative technologies.
  • Impact sound application of science within the company and beyond.
  • Publish in peer-reviewed journals and present at scientific meetings.
Qualifications:
  • PhD in data science or computational science, or other drug discovery related fields, with expert level training in data science, AI/ML and other in silico related work aligned to drug discovery is required.
  • At least 3 years of experience applying data science and technology in an industry facing drug design setting is required.
  • Experience working with data analytics and predictive modeling in the discovery of either large molecules, or small molecules is required.
  • Experience with both small and large molecules is preferred. Experience with Python is required.
  • Experience with data visualization, feature development, large language models, generative methods, are preferred.
  • Self-motivation, proactivity, team spirit, enthusiasm, confidence and dedication are required.
  • Experience with working in a cross-functional or matrixed team environment is required. Track record of planning and delivering on complex projects with a robust scientific footing is a plus.
  • Strong publication record is preferred.


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