Data Scientist

1 month ago


New York, United States VanderHouwen Full time

Software Developer for ML Data Engineering

Software developers who have experience working with complex data infrastructure and systems are sought to join our drug discovery software team in New York City. This role offers an exciting opportunity to create data infrastructure for our drug discovery and AI efforts, working closely with a world-class team of chemists, biologists, machine learning engineers and researchers, and computer scientists.


Successful hires will develop systems and infrastructure for modeling, curating, and indexing petabytes of data; implement pipelines for processing computational and experimental data sets; and develop/optimize workflows to deliver large data sets to machine learning training pipelines.


Ideal candidates will have a passion for large-scale data management; strong Python programming skills; and experience with machine learning systems, frameworks, and data lifecycles. Relevant areas of expertise include engineering of large-scale chemical databases, architecting workflows, and automating processes for the handling of life science data, fluency with Linux/UNIX tools, and familiarity writing scientific software, but specific knowledge of any of these areas is less critical than intellectual curiosity, versatility, and a track record of achievement. This is a unique opportunity to contribute to the development of transformative technology within a dynamic, interdisciplinary environment.


Relevant experience:

  • Demonstrated experience with large-scale data management in the life sciences (ideally dealing with chemistry databases)
  • Experience architecting infrastructure for the handling of life science data, and writing scientific software
  • Strong Python programming skills; C++ is a nice-to-have
  • Fluent knowledge of Linux/UNIX tools
  • Excellent communication skills


Responsibilities:

  • Develop systems and infrastructure for modeling, curating, and indexing petabytes of data
  • Implement pipelines for processing computational and experimental data sets
  • Develop/optimize workflows to deliver large data sets to machine learning training pipelines


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