Jobs at Root

Lead partner analytics by building scalable dashboards, forecasting and ROI models, and experimental designs to evaluate and optimize partner performance. Collaborate with Product, BD, Marketing, and Data Engineering to improve pipelines, translate insights into recommendations, and mentor analysts to scale partner growth.

Set technical direction for Root’s AI platform, including infrastructure, tooling, shared services, governance, reliability, security, observability, and cost management. Lead cross-team initiatives, guide AI and LLM architecture decisions, establish operating standards, shape technical roadmaps, resolve complex tradeoffs, and mentor engineers and technical leaders across the organization.

Lead the AI Platform team in building reliable, secure, observable infrastructure, shared services, deployment patterns, and operational practices for AI capabilities. Set technical priorities, coordinate cross-team dependencies, guide architecture and production operations, improve developer experience, and coach engineers while contributing to complex technical work.

Lead Root’s AI Enablement Squad by defining AI-native ways of working, guiding cross-team adoption, connecting user workflows to AI Platform strategy, and turning experiments into reusable products and capabilities. Set technical direction, lead major initiatives, align senior stakeholders, establish adoption measures, promote responsible AI use, and mentor engineers and technical leaders across the organization.

Lead the AI Enablement Squad by prioritizing embedded AI adoption engagements, translating workflow discoveries into reusable AI Platform improvements, coordinating cross-functional partners, and coaching engineers. Establish repeatable adoption playbooks, protect capacity for scalable capabilities, communicate outcomes and blockers to stakeholders, and guide responsible deployment of AI solutions across the company.

Lead development of Root’s machine learning platform for insurance pricing. Build and operate feature pipelines, model training and orchestration, registries, validation, serving, observability, and reproducibility tooling. Partner with researchers to convert experimentation into reliable production systems, explore LLM-enabled data science automation, drive technical roadmaps and execution, and mentor engineers while maintaining high standards for reliability and correctness.

Lead the architecture and development of Root’s machine learning platform for insurance pricing. Build infrastructure for feature pipelines and stores, reproducible training and orchestration, model registries, serving, validation, observability, and research-to-production workflows. Establish versioned contracts and technical standards, automate workflows using LLMs, write and review critical code, influence cross-team strategy, and mentor senior engineers. Collaborate closely with data scientists and researchers to create scalable, reliable, and reproducible ML capabilities.

Lead and develop a team of partnership analysts; translate business questions into analytical frameworks, experiments, forecasts, and ROI models. Build dashboards and reporting infrastructure, analyze cohorts, funnels, retention, and partner performance, and own measurement frameworks for growth initiatives. Partner with Business Development, Engineering, Product, and Marketing to shape partnership strategy and communicate data-driven insights to technical and non-technical leaders.

Analyze and optimize digital partnership performance, growth, profitability, and customer acquisition economics. Design experiments, develop forecasts and performance models, build measurement frameworks, investigate anomalies, and provide actionable recommendations. The role requires translating ambiguous business questions into analytical solutions, communicating insights to technical and non-technical stakeholders, and establishing scalable analytical processes that support strategic decision-making.

Leads Root’s Telematics Technology engineering domain, overseeing telematics data platforms, feature stores, trip pipelines, APIs, and customer-facing experiences. Responsibilities include setting technical strategy and roadmaps, partnering with Data Science, Pricing, and Underwriting, managing and developing engineering teams, recruiting, guiding distributed-system architecture, and improving reliability, observability, scalability, delivery processes, and production stability. The role also drives AI-tool adoption and may oversee production machine-learning systems.

Lead and scale Root's Financial Institutions vertical by owning the full partnership lifecycle: market strategy, enterprise pipeline, C-suite negotiations, implementation, executive governance, and long-term expansion. Build executive relationships with banks, credit unions, fintechs, and payment providers; structure commercial models using embedded insurance and SaaS capabilities; partner cross-functionally to prioritize product investments; and drive revenue, profitability, and forecasting.

Lead data science for Root's digital partnerships channel, managing a team to drive growth, profitability, experimentation, forecasting, optimization, and measurement. Partner with cross-functional teams to improve acquisition economics, influence product and technical roadmaps, deliver executive reporting, and establish scalable operating processes.

Lead and build a team that drafts and submits state-specific rating rules, underwriting guidelines, and forms; manage filing execution via SERFF, handle objection responses, coordinate cross-functional stakeholders, establish operating rhythms, improve documentation and controls, and coach staff to scale filing expertise and regulatory execution.

Lead and grow AI Platform and AI Enablement engineering teams building infrastructure, tooling, and integrations for AI features. Define AI engineering roadmap with product and data science partners, set standards for reliability, observability, security, and responsible AI, manage and develop engineers, engage in code/design reviews, and coordinate cross-team delivery with Platform and Data teams.

Lead technical strategy and execution for build, test, release, and deployment systems. Drive initiatives to improve developer productivity, deployment safety, and platform reliability. Coordinate cross-team projects and migrations, contribute high-impact code, coach engineers, and lead incident response and resilience improvements for shared engineering systems.

As a Lead Machine Learning Engineer at Root, you'll build scalable ML systems, partner with data scientists, and improve operational practices for customer lifetime value modeling.

Lead a multidisciplinary team to design, deploy, and optimize ML-driven bidding systems and measurement for a nine-figure marketing budget. Drive experimentation, partner strategy, media-mix optimization, and end-to-end measurement while aligning Marketing, Analytics, Engineering, and Product to improve marketing ROI and scale performance.

Drive growth in the Independent Agent channel by outbound prospecting, onboarding new agents, delivering product training, conducting business reviews, driving agent engagement, and collaborating with internal teams to improve agent experience and product adoption.