SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Ascend is a Series A fintech company building the first complete financial operations platform purpose-built for insurance. The platform combines AI-powered accounting automation, payments, and premium financing, serving over 4,000 businesses including more than half of the 50 largest insurance brokers in the country.
You will join as a Senior Data Scientist reporting to the Head of Data, owning measurement and decision-making across the product surfaces that move customer money. This is a high-impact role focused on accountability: you will settle metric definitions that currently have cross-team disagreement, set the thresholds that determine when the system acts autonomously versus routing to a human, and remain accountable for those thresholds in production.
In your first 30 days, you will immerse yourself in Ascend's products, data infrastructure, and the specific metric disagreements across Product, Engineering, and Data teams. You'll audit existing production scores and thresholds, and map instrumentation gaps.
By day 60, you will propose and settle accuracy, success, and exception metrics for all Ascend products. You'll own the thresholds that decide automation versus human routing, and partner with Product and Engineering on instrumentation for upcoming features.
Beyond 90 days, you will fully own all product metrics across the platform. You'll build and ship models that change workflows—confidence scoring on extracted data, ranking and matching for reconciliation, sequencing for collections. You'll monitor every score in production (predicted vs. realized, drift detection, re-fit/retire decisions), design experiments appropriate to the company's volume, and turn product usage data into roadmap input.
The role emphasizes operational rigor: you must be comfortable explaining calibration, drift, and re-fit timing to non-technical stakeholders, and you must be willing to say plainly when data is insufficient to support a decision.
REQUIREMENTS:
- Proven experience owning product data embedded in live workflows (not just reporting on them); ability to name the business decision your metric changed
- Deployed models into live workflows and owned post-deployment accountability (calibration, drift monitoring, re-fit/retire decisions)
- Strong SQL and feature engineering skills
- Comfortable explaining model concepts (calibration, drift, predicted-versus-realized, re-fit timing) to non-technical stakeholders
- Experience with payments systems is a plus
- Thrives in early-stage startup ambiguity; comfortable proposing next steps when data is weak
- Familiarity with Slack, Notion, Excel, Front, Linear
- Strong written and verbal communication; ability to quickly understand complex subject matter; attention to detail
