[Hiring] Lead Data Scientist @Root Insurance

Role Description

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

• Spend approximately 65% of time on Data Science and 35% on Data Engineering.
• Data Science responsibilities include:
  • Problem definition
  • Dataset development
  • Feature engineering
  • Statistical modeling
  • Model evaluation
  • Stakeholder validation
  • Regulatory support
  • Post-deployment monitoring
• Data Engineering responsibilities include:
  • Building and maintaining reliable modeling datasets
  • Improving data pipelines and transformations
  • Validating data quality and lineage
  • Productionizing models
  • Troubleshooting pipeline and system issues
  • Improving the reliability and maintainability of the Telematics data ecosystem
• Work across the full lifecycle of a telematics model—from raw data ingestion through model development, production deployment, monitoring, and ongoing operational support.
• Partner closely with Data Science, Data Engineering, Software Engineering, Pricing, Actuarial, Product, and Compliance teams to deliver reliable and 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 topics such as 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
• Ability to frame functional problem statements for the next 1-2 months, consistently making good decisions about the right path to follow in a well-defined problem space
• Experience using version control (e.g. Git) and cloud computing (AWS or analogous)

Requirements

• Strong knowledge of statistical modeling and machine learning methods, including GLMs, tree-based models, time-series analysis, feature engineering, model evaluation, resampling, and hyperparameter tuning.
• Familiarity with advanced methods such as neural networks, survival analysis, causal inference, or Bayesian modeling is preferred but not required.
• Demonstrated experience building and maintaining production-quality data pipelines, modeling datasets, and data transformations.
• Strong programming skills in Python and SQL, including the ability to write, test, review, and maintain production code.
• Experience with version control, automated testing, code review, CI/CD, and cloud-based data or machine learning systems.
• Experience validating data quality, lineage, completeness, consistency, and schema stability.
• Ability to troubleshoot issues across data, application, pipeline, and infrastructure layers.
• Experience deploying, monitoring, and maintaining production machine learning models.

Benefits

• Salary Range: $142,800 - $178,500 (Eligible for competitive bonus and equity offering)
• Work where it works best: Support for working in whatever location that works best across the US.