Data Scientist, Product

Ascend•San Francisco, CA

About The Position

Ascend is transforming the insurance industry, a $10T sector heavily reliant on outdated manual processes. We provide the first and only comprehensive financial operations platform designed specifically for insurance, integrating AI-powered accounting automation, payments, and premium financing. Our solution brings clarity to complex accounting operations, from collection to close. We have become the market leader in five years, trusted by over 4,000 businesses, including more than half of the top 50 brokers in the country. Our platform automates daily financial operations for insurers, MGAs, and agencies, embedding directly into transactions. We believe AI is driving down software costs, and companies that capture value at the point of transaction will win. Ascend customers achieve significant efficiency gains with a proven 5-7x return on investment. Our approximately 100-person team, based in San Francisco and Columbus, comprises experts in insurance, fintech, and AI, dedicated to building essential industry infrastructure. Our mission is to become the leading financial automation platform for insurance by 2030, powering the industry's financial operations and revolutionizing how trillions of dollars are managed. We are building the financial backbone of the insurance industry, not just another point solution.

Requirements

Owned product data inside a live workflow rather than reporting on one, and can name the decision your number changed.
Deployed a model into a live workflow and owned it afterward, including calibration, drift, and the call to re-fit or retire.
Comfortable explaining calibration, drift, predicted-versus-realized, and re-fit timing to a non-technical owner.
Strong in SQL and feature engineering.
Experience with payments is a plus.
Thrives in the ambiguity of an early-stage startup and will say when the data is too weak to decide, then propose a next step anyway.
Experience working in our toolset: Slack, Notion, Excel, Front, and Linear.
Strong written and verbal communication skills.
Ability to quickly understand complex subject matter.
Great attention to detail.

Responsibilities

Settle metric definitions that three teams currently disagree on.
Set thresholds that decide when a human touches a document.
Stay accountable for those thresholds after they go live.
Get deep into Ascend's products, data infrastructure, and metric definitions.
Build relationships with Product, Engineering, and the Head of Data to understand measurement decision-making.
Audit production scores and thresholds and map missing instrumentation.
Propose and settle accuracy, success, and exception metrics for Ascend's products.
Own thresholds that determine system actions versus human routing.
Partner with Product and Engineering on instrumentation for upcoming features.
Fully own accuracy, success, and exception metrics across all products.
Build and ship models that change workflows (e.g., confidence scoring, ranking/matching, sequencing).
Monitor production scores (predicted vs. realized, drift, re-fit/retire dates).
Design experiments that volume can support.
Turn product usage data into roadmap input.