7 months ago
Statistical modeling and hypothesis testing.
Designing, training, and validating results from a breadth of machine learning algorithms.
Writing clean, efficient SQL.
Integrating with various RDBMS (e.g., Postgres, MySQL) and distributed data stores (e.g., Hadoop).
Building Python applications.
Deploying applications into cloud-based infrastructures (e.g., AWS).
Building deep neural networks with modern tools, such as PyTorch or Tensorflow.
Creating and interacting with RESTful APIs.
Managing *nix servers.
Writing unit tests.
Collaborating via Git.