About the Company
Valon is building the AI-native operating system for regulated finance, starting with mortgage servicing.
We're a Series C company backed by a16z, transforming industries that others have written off as too complex to innovate.
Rather than build on top of broken legacy systems, we took a different approach: we built and operate our own mortgage servicing business managing $110+ billion in loans. This wasn't the end goal, it was how we deeply understood the complexity needed to build software that actually works in regulated industries.
The results speak for themselves. We've transformed mortgage servicing from a 0% margin business into 60%+ margins while dramatically improving customer experience. Major enterprise contracts are now deploying across the industry.
ValonOS is our unified platform that makes every process structured and programmable and it is perfectly positioned for the AI era. When everything flows through one system with rich data, AI agents don't just automate tasks, they continuously improve entire operations. Mortgage servicing is just the beginning of our vision to transform regulated industries and beyond.
About the Role
We are looking for full-stack data analysts who can take end-to-end ownership of the data and analytics needs of Valon’s SaaS customers. You will be responsible for large scale migrations of varying reporting infrastructure to the Valon Data Schema and API on behalf of clients. You will interface with clients, stand up data infrastructure, migrate or build out reporting, and more. You'll own the data side of every implementation end-to-end: requirements, infrastructure, migration, and the analytical relationship that follows.
Responsibilities
Collect and document client requirements at the project level from client data analysts.
Establish new data processes, tools, and systems for clients according to plan.
Create reporting pipelines in dbt.
Write, re-write, or migrate SQL queries, reports, and dashboards to empower client operational processes.
Conduct analysis to inform client business decisions.
Document, audit, and improve client data sets to meet client data needs.
Respond to data requests from the client and their operations teams.
Meet tight project deadlines.
Dive deep into the mortgage servicing industry to understand its complicated inner workings.
Develop expert level AI skills to code at maximum velocity.
Ideal Background
6-8+ years of full-time work experience in data analytics, product analytics, business analytics, or business intelligence, ideally at a tech company (mortgage servic