Senior Data Scientist [Remote-US]

About Us

The role

We’re looking for a Data Scientist with a strong engineering and operations mindset to help us build scalable, innovative personal auto risk and telematics models. In this role, you’ll go beyond modeling: you’ll architect robust pipelines, develop libraries used by multiple teams, and champion best practices for version control, testing, and deployment. Reporting to our Data Science Director, you’ll be instrumental in developing new risk models that align with Quanata’s mission to revolutionize transportation risk prediction. Your experience in software engineering and/or data engineering will be crucial as you work alongside a collaborative, cloud-based data science team.

Your day-to-day

1. Architect & Develop: 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.Technical Leadership: 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.
2. Cross-Functional Collaboration: Partner with actuarial, product, and engineering teams to translate complex models and analytical tools into scalable, real-world applications that add measurable business value.
3. End-to-End Ownership: 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.
4. Stakeholder Communication: Present analytical findings and operational roadmaps to senior leadership. Demonstrate how sound engineering practices and data-driven insights can inform strategic business decisions.
5. Infrastructure & Tooling: Lead efforts to optimize and automate cloud-based data science environments, establishing guidelines for resource utilization, environment provisioning, and production deployments.
6. Innovation & Continuous Improvement: 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.

About you

• Educational Background: Bachelor’s or Master’s degree (or equivalent professional experience) in a quantitative field, Computer Science, or related discipline.
• Relevant Experience: 12 years of combined experience in data science and/or data engineering, with a track record of building and maintaining complex data pipelines or libraries.
• Technical Proficiency: 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.
• Independent & Collaborative: Able to drive projects independently from start to finish, yet comfortable working with diverse teams to integrate solutions across the organization.
• Modeling & Analytics: Deep knowledge of machine learning algorithms and data science methodologies, with an ability to deploy models in a production setting.
• Communication: Adept at translating technical concepts into clear, concise messages for non-technical stakeholders and senior leadership.
• Passion for Quality & Speed: You thrive on shipping high-quality models, tools, and features frequently, maintaining a culture of agility and reliability.

Bonus points

• Advanced Credentials: PhD in a quantitative discipline or an actuarial designation (or progress toward one).
• Industry Experience: Prior experience in auto insurance, specifically in cost modeling and working with large-scale, semi-structured or unstructured datasets.
• Telematics Know-How: Hands-on experience with telematics data collection, signal processing techniques, or IoT data pipelines.
• Open-Source Contributions: Demonstrated track record of contributing to open-source projects or maintaining widely used analytical libraries.

Salary: $250,000 to $450,000*

*Please note that the final salary offered will be determined based on the selected candidate's skills, and experience, as well as the internal salary structure at Quanata. Our aim is to offer a competitive and equitable compensation package that reflects the candidate's expertise and contributions to our organization.

Additional Details: 

• Benefits: We provide a wide variety of health, wellness and other benefits.These include medical, dental, vision, life insurance and supplemental income plans for you and your dependents, a Headspace app subscription, monthly wellness allowance and a 401(k) Plan with a company match.
• Work from Home Equipment: Given our virtual environment— in order to set you up for success at home, a one-time payment of $2K will be provided to cover the purchase of in-home office equipment and furniture at your discretion. Also, our teams work with MacBook Pros, which we will deliver to you fully provisioned prior to your first day.
• Paid Time Off: All employees accrue four weeks of PTO in their first year of employment.  New parents receive twelve weeks of fully paid parental leave which may be taken within one year after the birth and/or adoption of a child. The twelve weeks is applicable to both birthing and non-birthing parent.
• Personal and Professional Development: We’re committed to investing in and helping our people grow personally and professionally.  All employees receive up to $5000 each year for professional learning, continuing education and career development.  All team members also receive LinkedIn Learning subscriptions and access to multiple different coaching opportunities through BetterUp.
• Location: We are a remote-first company for most positions so you may work from anywhere you like in the U.S, excluding U.S. territories. Occasional travel may be required for team meetings or company gatherings. Employees based in the San Francisco Bay Area or in Providence, Rhode Island may commute to one of our local offices as desired.  
• Hours: We maintain core meeting hours from 9AM - 2PM Pacific time for collaborating with team members across all time zones.