About the job
Arlo is revolutionizing the health insurance landscape by leveraging AI technology. The current healthcare journey can be both costly and perplexing, often leading individuals to postpone essential care. Our mission is to redefine health plans as proactive allies in promoting wellness rather than obstacles to it. Our AI-driven platform provides ongoing, tailored support for our members, guiding them through benefits, appointment scheduling, access to top-tier care, and alleviating financial anxieties. With a cutting-edge risk-pricing engine at its core, Arlo is rapidly expanding, achieving $XXXM in premiums and servicing tens of thousands, with increasing demand from brokers, employers, and partners. Supported by prominent investors such as Upfront Ventures, 8VC, and General Catalyst, our team blends extensive industry knowledge from companies like Palantir and Y Combinator, with the vision to modernize a $1 trillion market.
The Opportunity
We are seeking a Head of Data Infrastructure & Ontology who will architect, oversee, and expand the data systems that are fundamental to Arlo’s products and strategic decisions. This pivotal role involves taking complete ownership of critical data infrastructure, transforming disparate data sources into cohesive, intelligent, and highly automated systems. You will play a key part in shaping the operational future of an AI-driven insurance provider.
What You Will Do
- Manage Arlo’s comprehensive data infrastructure — from data ingestion to modeling and analytics — ensuring scalability, reliability, and support for real-time business decisions.
- Advance our underwriting, pricing, and financial data systems by converting complex inputs (claims, rates, demographic data, TPA feeds) into clean, reliable, automated pipelines.
- Design and sustain Arlo’s core data models and “source of truth” tables that facilitate reporting, high-cost claimant identification, case management signals, and deliverables for partners.
- Establish and standardize data ingestion processes for both internal and external data sources, including various TPAs, carriers, and partner systems.
- Foster intelligence throughout the organization by developing abstractions, automations, and reasoning layers that enhance pricing strategies, renewals, cost management, and care navigation.
- Collaborate closely with engineering, underwriting, data science, operations, and product teams to promote data consistency, governance, and transparency across the organization.
- Provide technical leadership and hands-on executive support to drive data initiatives forward.

