Associate Data Scientist

Unpaid

Volunteer

Part-Time

Remote

Our team of part-time volunteers works with machine learning, deep learning, and signal analysis for audio analysis in a medical setting. We welcome individuals with professional experience in these domains to apply. The candidate will be immersed in a collaborative environment alongside AI engineers and mentors.

Responsibilities

  • Deeply research and identify state-of-the-art ML approaches for detecting COVID from coughs.
  • Train, build, and deploy AI models into production.
  • Produce clean code and APIs to facilitate understanding within the team.
  • Collaborate with product management and leadership to deliver on expectations.
  • Build data ingest and data transformation infrastructure.
  • Process and feature extract from a wide array of input data types.
  • Identify transfer learning opportunities and auxiliary training datasets.
  • Distill results into academic formats, e.g. research paper.

Requirements

  • 1-2 years of experience of CS/ML coursework and prior internship experience.
  • Passionate and committed to the Virufy mission, communicate effectively, and share learnings with the team.
  • Strong Python programming experience with toolkits such as Pandas, NumPy, Librosa.
  • Experience in training models with frameworks like Scikit-learn, Tensorflow, Pytorch, Keras.
  • Hands-on AI programming experience working on (ideally) enterprise products.
  • Experience using AI for healthcare in clinical research studies and solving real-world problems.

Hours

  • 5-15 hours per week

Questions?

Virufy complies with the Immigration Reform and Control Act (IRAC). Virufy is an equal opportunity, volunteer-run, 501(c)(3) non-profit organization, and all qualified applicants will receive consideration for a volunteer opportunity without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by any applicable Federal, State, local, or international laws.

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