Lead Data Scientist, Telematics

Root Inc.

. Develop and maintain telematics pricing and underwriting models .

Posted 9/30/2026full-timeRemote • United StatesSenior💰 $142,800 - $178,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and maintaining telematics pricing and underwriting models, with a strong focus on statistical modeling, machine learning, and data pipeline management. Proficient in ensuring compliance with regulatory requirements while delivering high-quality, production-ready models.

Highest-signal resume keywords

Statistical ModelingMachine LearningPython ProgrammingData Pipeline ManagementRegulatory Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingMachine LearningFeature EngineeringModel EvaluationData Pipeline DevelopmentData TransformationHyperparameter TuningData Quality ValidationNumerical OptimizationTime-Series Analysis

Soft Skills

Data VisualizationCommunication Skills

Tools & Technologies

PythonSQLGitAWSCI/CD

Certifications & Qualifications

Advanced Degree in Quantitative Discipline

Industry Keywords

TelematicsInsurance ConceptsLoss RatiosClaims FrequencyRegulatory Requirements

Tech Stack

Tools & technologies

AWSCloudPythonSQL

About the role

Key responsibilities & impact

Develop and maintain telematics pricing and underwriting models
Define problems, develop datasets, engineer features, build statistical models, evaluate models, validate with stakeholders, support regulatory requirements, and monitor post-deployment performance
Build and maintain reliable modeling datasets, data pipelines, and transformations
Validate data quality and lineage
Productionize models and troubleshoot pipeline and system issues
Improve the reliability and maintainability of the Telematics data ecosystem
Manage the full telematics model lifecycle from raw data ingestion through development, production deployment, monitoring, and operational support
Partner with Data Science, Data Engineering, Software Engineering, Pricing, Actuarial, Product, and Compliance teams
Introduce new statistical algorithms and modeling techniques; prototype, test, retest, and scale approaches
Adopt and refine modeling best practices, documentation standards, and peer reviews
Provide modeling support, documentation, and explainability to state regulators
Ensure statistical models comply with state-specific regulatory requirements and constraints

Requirements

What you’ll need

Advanced degree in a quantitative discipline and/or 5+ years of applying advanced quantitative techniques to industry problems
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
Strong programming skills in Python and SQL
Demonstrated experience building and maintaining production-quality data pipelines, modeling datasets, and data transformations
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
Strong knowledge of statistical modeling, machine learning, and numerical optimization
Strong data visualization and communication skills
Demonstrated experience building, validating, and applying statistical machine learning methods to real-world problems
Experience using version control such as Git and cloud computing such as AWS
Ability to frame functional problem statements for the next 1–2 months and make decisions in a well-defined problem space
Ability to work on camera for virtual interviews
Preferred but not required: PhD; neural networks, survival analysis, causal inference, or Bayesian modeling; insurance experience; familiarity with insurance concepts such as loss ratios, loss cost, and claims frequency

Benefits

Comp & perks

Competitive bonus
Equity offering
Work from any location across the US
Reasonable accommodation for qualified applicants with disabilities