Senior Data Scientist

Job summary

The role involves owning production models from design to deployment, ensuring they are robust and scalable. The Senior Data Scientist will work closely with software and data engineers to maintain operational precision and implement best practices in a high-autonomy environment.

Qualifications

• Significant experience in applying data science to production problems, with a focus on ownership rather than years of experience.
• Strong proficiency in Python and software engineering practices, including version control and CI/CD.
• Solid experience in MLOps, covering deployment, monitoring, versioning, and drift detection.
• Expertise in model evaluation and validation, including backtesting and uncertainty estimation.
• Familiarity with AWS and CI/CD pipelines.
• Background in optimization or operations research is advantageous.
• Experience in designing data layers or feature stores is a plus.
• Domain knowledge in commodities, freight, shipping, logistics, energy, or finance is beneficial but not essential.

Responsibilities

• Manage models end-to-end, ensuring they are tested and monitored in production on AWS.
• Oversee the full operational lifecycle of models, including deployment and lifecycle management.
• Integrate evaluation and validation into models, ensuring clarity on their limitations.
• Collaborate on designing a common data layer and evaluate abstraction layers for models.
• Lead CI/CD processes for the model codebase, including testing and code reviews.
• Share best practices across the growing team.

Skills

• Strong analytical and problem-solving skills with a focus on ownership and intellectual curiosity.
• Ability to make design decisions independently and proactively learn new tools.

Education

• A degree in a relevant field is typically expected, though specific educational requirements are not detailed.

Tools

• Proficiency in Python, AWS, and CI/CD tools.