Lead Data Scientist, Telematics & ML Ops

joinroot; United States; Remote; USD 143,000 - 179,000; Full time

Benefits offered by this job

Bonus

Equity

Job summary

Root in the United States is seeking a Lead Data Scientist I to support the Telematics Data Science team. This hands-on role focuses on developing and maintaining telematics pricing and underwriting models, with significant responsibility for data engineering and production systems.

The role will spend 65% on Data Science and 35% on Data Engineering, collaborating with Pricing, Actuarial, Product, and Compliance to deliver measurable business outcomes.

Qualifications

• Advanced degree in a quantitative discipline (PhD preferred) and/or 5+ years of applying advanced quantitative techniques to problems in industry
• Strong demonstrable knowledge of statistical modeling, machine learning, and numerical optimization
• Exceptional communicator and storyteller with strong data visualization skills
• Strong programming skills with experience in SQL and Python
• Demonstrated experience building, validating, and applying statistical machine learning methods to real world problems
• Demonstrates ownership mentality, taking initiative to find, prioritize, and be accountable for the highest impact work

Responsibilities

• Develop and maintain telematics pricing and underwriting models.
• Build and maintain reliable modeling datasets and data pipelines.
• Prototype, test, retest and scale modeling approaches.
• Collaborate with Data Science, Data Engineering, Software Engineering, Pricing, Actuarial, Product, and Compliance teams.
• Productionize models and monitor performance in live systems.

Skills

Statistical modeling

Machine learning

Python

SQL

Data visualization

Education

PhD preferred

5+ years applied experience

Tools

Git

AWS

CI/CD

Job description

Root in the United States is seeking a Lead Data Scientist I to support the Telematics Data Science team. This hands-on role focuses on developing and maintaining telematics pricing and underwriting models, with significant responsibility for data engineering and production systems.

The role will spend 65% on Data Science and 35% on Data Engineering, collaborating with Pricing, Actuarial, Product, and Compliance to deliver measurable business outcomes.