Senior Data Scientist [Remote-US]

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Requirements:

• Strong Python and SQL skills, especially in cloud-based environments (AWS, Azure, GCP).
• Familiarity with software engineering best practices (version control, code reviews, CI/CD, containerization) is critical.
• Deep knowledge of machine learning algorithms and data science methodologies, with an ability to deploy models in a production setting.

Responsibilities:

• Lead the design, development, and maintenance of advanced personal auto insurance risk models and foundational data pipelines.
• Create modular, reusable components and libraries that enhance the efficiency and scalability of our modeling process.
• Mentor fellow data scientists and data engineers by encouraging best practices for code structure, version control, CI/CD, testing, and reproducibility.
• Review pull requests and champion code quality across the data team.
• Partner with actuarial, product, and engineering teams to translate complex models and analytical tools into scalable, real-world applications that add measurable business value.
• Manage the full project lifecycle—from requirements gathering and architecture to deployment and monitoring—ensuring solutions are robust and optimized for performance in cloud-based environments.
• Present analytical findings and operational roadmaps to senior leadership. Demonstrate how sound engineering practices and data-driven insights can inform strategic business decisions.
• Lead efforts to optimize and automate cloud-based data science environments, establishing guidelines for resource utilization, environment provisioning, and production deployments.
• Stay current with emerging technologies in data engineering, MLOps, and machine learning. Continuously evaluate and integrate new techniques to keep Quanata at the cutting edge of risk prediction.