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Machinify

AI-driven healthcare operations optimization platform

Senior Data Scientist - Modeling

Applied Machine LearningPosted on Nov 10
Full-timeRemote in USA

About the Job

Requirements

  • Experience successfully solving real-world business problems involving data-driven optimization and machine-learning modeling.
  • Ability to measure and optimize the direct business impact of work.
  • Experience using SQL and handling large-scale data, and proficiency in at least one programming language such as Python or R.
  • Experience building machine-learning models from scratch for new applications using approaches such as neural networks or tree ensembles, including choosing supervised labels, optimization metrics, and useful features.

Responsibilities

  • Analyze clinical and coding audits, the data driving audit decisions, and past outcomes.
  • Curate labeled data, hypothesize new features, and develop machine-learning models to identify claims for audit with greater precision.
  • Measure model performance rigorously and translate outcomes into operational insights and recommendations for clients.
  • Refine complex, often unclean and undefined, data pipelines derived from business workflows for robust modeling.
  • Enhance data pipelines, modeling infrastructure, and team tools to improve capabilities and decision-making efficiency.
  • Build expertise in healthcare data and engage with clients and internal experts to refine model insights and align them with business needs.

About the Company

Machinify

AI-driven healthcare operations optimization platform

Machinify uses artificial intelligence to optimize decision-making in healthcare. It provides AI-driven applications that improve operational efficiency for health plans, payers, and providers, acting as a central nervous system to manage data-driven decisions. Its products streamline processes like claims processing and utilization management by deploying a growing portfolio of applications on the Machinify platform, designed for fast implementation and immediate ROI. Differences from competitors include an AI-first platform tailored to healthcare administration, a rapid deployment model, and a customer-focused approach that aims to deliver tangible results quickly. The company’s goal is to transform healthcare administration by reclaiming control over healthcare expenditures and improving efficiency and patient outcomes through data-driven decisions.

Company size
1,001-5,000
Company stage
Series A
Total funding
$15.6M
Headquarters
Palo Alto, CA
Founded
2016

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