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Root Insurance

Direct-to-consumer auto insurer with telematics

Lead Data Scientist - Telematics

Data Science +1Updated on Nov 12
Full-timeRemote in USA

About the Job

Requirements

  • Strong knowledge of statistical modeling and machine learning methods, including generalized linear models, tree-based models, time-series analysis, feature engineering, model evaluation, resampling, and hyperparameter tuning.
  • 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, continuous integration and continuous delivery, 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.
  • Advanced degree in a quantitative discipline or 5+ years of applying advanced quantitative techniques to problems in industry.
  • Strong demonstrable knowledge of statistical modeling, machine learning, and numerical optimization.
  • Strong data visualization skills.
  • Demonstrated experience building, validating, and applying statistical machine learning methods to real-world problems.
  • Ability to frame functional problem statements for the next 1–2 months and make decisions about the right path in a well-defined problem space.
  • Experience using version control such as Git and cloud computing such as AWS or analogous platforms.
  • Candidates must be on camera for virtual interviews.

Responsibilities

  • Develop and maintain telematics pricing and underwriting models, with a significant secondary responsibility for the data engineering and production systems that support the models.
  • Define problems, develop datasets and features, perform statistical modeling and model evaluation, validate models with stakeholders, support regulatory needs, and monitor models after deployment.
  • Build and maintain reliable modeling datasets; improve data pipelines and transformations; validate data quality and lineage; productionize models; troubleshoot pipeline and system issues; and improve 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 with Data Science, Data Engineering, Software Engineering, Pricing, Actuarial, Product, and Compliance teams to deliver reliable and measurable business outcomes.
  • Work closely with Product Management, Pricing, and Actuarial teams to align Data Science models with product and pricing considerations.
  • Introduce new statistical algorithms and modeling techniques; prototype, test, retest, and scale approaches.
  • Adopt and refine modeling best practices, documentation standards, and peer reviews.
  • Ensure statistical models comply with state-specific regulatory requirements and constraints.
  • Provide modeling support, documentation, and explainability to state regulators.

Desired Qualifications

  • Familiarity with neural networks, survival analysis, causal inference, or Bayesian modeling.
  • Experience in one or more insurance lines, including property and casualty, life, health, or specialty insurance.
  • Familiarity with insurance concepts such as loss ratios, loss cost, and claims frequency.
  • PhD.

About the Company

Root Insurance

Direct-to-consumer auto insurer with telematics

Root Insurance sells auto insurance through a digital-first direct-to-consumer model. It uses telematics from a smartphone to rate premiums based on driving behavior, rewarding good drivers with personalized rates. By cutting agents and relying on data, it lowers costs and passes savings to customers. Its goal is to make auto insurance affordable and easy for good drivers through a transparent, data-driven approach.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Columbus, OH
Founded
2015

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