TL;DR

Lead Data Scientist (Fraud Waste Abuse): Lead strategic data science initiatives to detect and prevent healthcare fraud, waste, and abuse by analyzing healthcare and product data. Focus on advanced statistical modeling, data mining, and presenting actionable insights to leadership.

Location: Fully remote within the United States with about 5% travel

Salary: $148,000 to $175,000 annually

Company

%hirify_global% delivers AI-powered clinical intelligence solutions improving payer-provider collaboration and healthcare economics, recognized as a top startup and backed by leading investors.

What you will do

Drive data science projects focused on preventing and identifying healthcare fraud, waste, and abuse
Lead analyses of healthcare claims and authorization data to detect suspicious activities
Serve as subject matter expert on fraud detection and regulatory compliance
Maintain detailed methodology documentation and present findings to leadership
Use data visualization to communicate insights and propose business solutions

Requirements

Must be located in the United States or authorized to work remotely within the US
MSc or higher in data science, statistics, mathematics, or related field
7+ years of data science experience in healthcare insurance or related field
Expertise in healthcare claims, coding, reimbursement, and fraud investigation regulations
Proficiency in Python, PySpark, Scala, or Spark SQL programming
Strong communication skills to translate between business, clinical, and technical teams

Nice to have

Experience with graph databases managing clinical concepts
Familiarity with Amazon AWS cloud platform

Culture & Benefits

Fully remote work with minimal travel
Comprehensive medical, dental, vision, life, and disability insurance
401K retirement plan with company match and flexible spending accounts
Up to 23 days PTO plus company holidays and paid parental leave
Pet insurance and Employee Assistance Program

Hiring process

Preliminary phone screening with Talent Acquisition
Interview with Hiring Manager
Take-home assessment
Case study presentation
Behavioral interviews