- Master’s or Ph.D. in a quantitative field (Mathematics, Statistics, Physics, Computer Science, Operations Research, Industrial Engineering, Electrical Engineering).
- Proven experience in applied science, machine learning, or data science roles, including experience deploying ML models in production environments.
- Proven experience with deep learning, representation learning, embedding models, or self-/semi-supervised learning.
- Fluency in Python and SQL (or similar scripting languages). Experience with big data technologies such as Apache Spark.
- Working knowledge of machine learning modeling/computation frameworks such as PyTorch or Tensorflow.
- Demonstrated ability to work independently, rapidly prototype solutions, and test new ideas.
- Strong communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.