Jobs at Arlo

• Validate inputs derived from broker submissions and external documentation; correct errors directly where appropriate and escalate systemic issues to the data science team for resolution.
• Monitor underwriting funnel performance, including quote volume, close ratios, quote-to-bind conversion, and broker and segment mix; identify and communicate the drivers behind observed trends.

• Build and own the infrastructure layer that powers our underwriting model, trained on tens of millions of patients and hundreds of millions of rows of claims data.
• Make training reliable, reproducible, and scalable as data volume and model complexity grow.

• Develop a robust evaluation framework to stress the model outcomes and identify specific gaps in risk estimates (cohorts, conditions, or claims patterns) and the underlying causal factors
• Use those findings to generate a roadmap of model and feature work that is prioritized based on making sure our rates are competitive in the market while ensuring we can remain a profitable business.

• Population Health Strategy: Identify key needs across Arlo’s member populations and develop scalable, data-driven programs to improve outcomes and reduce the total cost of care.
• Care Navigation Models: Help guide how Arlo’s concierge and care support services proactively engage members—especially those with complex or rising risk conditions.

• Build and ship delightful, AI-powered features across our web and mobile applications (React, React Native, TypeScript).
• Partner with our AI team to integrate sophisticated LLM agents into seamless, conversational user interfaces.

• Build and own the infrastructure layer that powers our underwriting model, trained on tens of millions of patients and hundreds of millions of rows of claims data.
• Make training reliable, reproducible, and scalable as data volume and model complexity grow.

• Own the data pipelines & system end to end: data ingestion, model training & inference, and serving results via API to our quoting frontend and manage the underlying infrastructure.
• Work closely with Sean Chin, Head Actuary, to translate business and actuarial priorities into scoped, executable work for the data team.

• Design and ship full-stack products across the insurance lifecycle, working across React, React Native, TypeScript, Python, Postgres, and modern AI infrastructure.
• Build AI-native underwriting systems that synthesize risk, structure messy data, and assist decision-making.

• Build and ship delightful, AI-powered features across our web and mobile applications (React, React Native, TypeScript).
• Partner with our AI team to integrate sophisticated LLM agents into seamless, conversational user interfaces.

• Design and ship full-stack products across the insurance lifecycle, working across React, React Native, TypeScript, Python, Postgres, and modern AI infrastructure.
• Build AI-native underwriting systems that synthesize risk, structure messy data, and assist decision-making.

• Craft and test messaging that resonates with our target audiences — customers, advisors, and partners.
• Build, run, and optimize campaigns across digital and offline channels:

Meta and LinkedIn Ads
Direct Mail
SEO & content programs
Generative-AI-driven creative and landing page testing