Careers

AT WHITEHATAI, THE WORLD’S MOST TALENTED AND CREATIVE ENGINEERS, DESIGNERS, AND THOUGHT LEADERS ARE CHANGING THE GAME IN HEALTHCARE FRAUD DETECTION TECHNOLOGY. THAT TAKES TALENT. YOUR TALENT.
IF YOU ARE READY TO RUN WITH WHITEHATAI TOWARDS THE FUTURE BY PUSHING BOUNDARIES, CREATING, QUESTIONING, GROWING, INNOVATING, AND DISRUPTING AN ENTIRE INDUSTRY, LET’S TALK.

The 2020 U.S. healthcare fraud, waste and abuse (FWA) crisis in the U.S. is estimated to cost $800 Billion, and growth of FWA is forecast to outpace that of healthcare overall. Healthcare FWA in the U.S. is estimated to make up 20% of an ever-increasing $4.1 trillion healthcare industry, almost all of which goes undetected. 

The volume, variety, and complexity of healthcare transactions has created a “perfect storm” for FWA. As the FWA problem in the U.S. grows, it increasingly endangers patients and their access to care.

WhiteHatAI is working with Special Investigations Units (SIU) for major U.S. payers who believe fraud alone in their organizations accounts for 10% of their total healthcare claims transaction volume. These units are currently recovering less than 2% of their fraud, leaving billions of dollars in losses. 

The rules-based, retrospective, analytic systems currently used have proven insufficient in combating FWA. The market is missing the critical ingredient for fighting FWA prepayment; a flexible prepayment solution that moves investigative efforts from post payment to prepayment. This need creates a tremendous opportunity. The market is searching for the prepayment Artificial Intelligence (AI) approach provided by WhiteHatAI. The combination of the maturity of AI technologies and increasing FWA makes this the perfect time for WhiteHatAI. 

 

JOB DESCRIPTION
WhiteHatAI Data Analytics team is looking for a Statistician/Data Scientist. In this role, you will engineer and implement production code to generate insights from data across the company and its customers. You’ll engage in a variety of projects that will build your analytical skills across a wide spectrum of areas.. As a Statistician/Data Scientist, you will help us build the next generation of data-driven decision making tools for our distributed analytics applications.  

The focus of this position is to research, engineer and develop software and methods to find fraud, waste and abuse in health insurance claims. You will use a combination of mathematics, statistics, statistical learning and software engineering to recover savings for health insurance industry members, providers and payers.

 

QUALIFICATIONS

  • Fluency in statistics and statistical methods
  • Demonstrable background of applying known statistical and engineering techniques to solve novel problems
  • History of delivering code and statistical solutions for enterprise applications
  • Experience with a variety of statistical learning techniques such as decision trees, random forest, logistical regression, clustering, taxonomies, statistical classifications, etc.
  • Excellent programming skills in Python and SQL: sqlalchemy a big bonus 
  • Passion for clean, flexible and well-documented code 
  • Experience designing and developing for security critical applications; experience with the specifics for HIPAA/PHI/PII/GDPR a big plus
  • Experience developing data offerings using R Shiny, Plot.ly/Dash or Flask
  • Basic experience with Linux is helpful
  • Extensive experience with Git
  • Knowledge of Agile development practices
  • Demonstrable ability to document solutions clearly and concisely
  • Flexibility and adaptability to respond to a rapidly changing environment
  • Experience with distributed computational techniques and job orchestration tools and platforms is very valuable: joblib, airflow, cadence, etc.

EXPERIENCE

  • 5+ years’ experience in data analytics, data science, quantitative analysis using statistical computer languages (R, Python, SLQ, etc.) to draw insights from large data sets 
  • 4+ years of Python development, preferably delivering production code for data applications

EDUCATION

  • MS or PHD degree in statistics, bio-statistics, bioinformatics, computational biology, mathematics, operations research, or in a fundamentally quantitative field, such as physics , economics, computer science, electrical engineering, and many years of delivering statistical or statistical learning solutions.