Staff Data Scientist | Modeling

United StatesRemote

You are nearing today's limit. Upgrade for unlimited access.

Responsibilities

Optimize Impact: Measure model performance rigorously, translating outcomes into operational insights and recommendations for our clients. •
Drive Team Success: Enhance data pipelines, modeling infrastructure, and team tools to level up our capabilities and decision-making efficiency. •
Grow with Healthcare: Build expertise in healthcare data and make an impact on the industry.

Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise.
Our team builds machine learning models for some of the largest health plans in the country to identify and audit claims errors from simple errors to outright fraud.
Master Claim Audits: Dive into various clinical and coding audits, unpacking the data that drives audit decisions, and understanding past outcomes. •
Model Advancement: Curate labeled data, hypothesize new features, and develop ML models that target claims for audit with even greater precision. •
You enjoy solving real-world business problems involving data-driven optimization and ML modeling - and have been doing that successfully for a while. •
You are experienced with SQL, handling large-scale data, and are comfortable with at least one programming language (Python, R, etc.). • You have
experience building ML models using modern ML approaches like Neural Nets or Tree-ensembles from scratch for new applications - making decisions relating to which supervised labels to use, the metric to optimize for, and the features likely to be useful

We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
Large insurance payers receive tens of millions of claims each year, of which they only are able to audit less than 10%.
Our claim selection models help with selecting the right set of claims to audit and recover hundreds of millions of dollars each year reducing wasted medical spend.