Staff Data Scientist - Remote

Overview

Machinify is the leading provider of AI-powered software products that transform healthcare claims and payment operations. Each year, the healthcare industry generates over $200B in claims mispayments, creating incredible waste, friction and frustration for all participants: patients, providers, and especially payers. Machinify’s revolutionary AI-platform has enabled the company to develop and deploy, at light speed, industry-specific products that increase the speed and accuracy of claims processing by orders of magnitude.

In Short

• 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.
• Optimize Impact: Measure model performance rigorously, translating outcomes into operational insights and recommendations for our clients.
• Tame Complexity: Work with vast, nuanced data pipelines derived from intricate business workflows—often unclean and undefined—to refine them for robust modeling.
• 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. Engage with clients and internal experts to refine model insights, ensuring alignment with real business needs.

Requirements

• 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 comfortable measuring and optimizing the direct business impact of work.
• 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.

Benefits

• Meaningful equity
• Excellent healthcare
• Flexible time off
• Other benefits and perks