Xenolytix is seeking a data scientist to join our team in developing machine learning solutions, building statistical models, and generally helping our clients discover value in their data.
This role thus requires a deep expertise in applying statistics and machine learning to real-world problems where data must be gathered, transformed, cleaned, and integrated into a larger architecture.
Candidates will be evaluated based on their experience in the following areas (though no one is expected to be an expert in all of these):
- 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
- Building, testing, and deploying computer vision based solutions
- Building, testing, and deploying reinforcement learning based solutions
- Creating and interacting with RESTful APIs
- Managing *nix servers
- Writing unit tests
- Collaborating via Git
Applicants with a PhD in a quantitative field are preferred; however, all applicants will be considered based on their experience and demonstrated skill/aptitude.