Senior Data Scientist
Location: Remote - USA (Open to applicants from multiple states, including Alabama, Florida, Texas, and more)
About the Company:
Join a rapidly growing, private equity-backed leader in healthcare cost recovery, dedicated to helping hospitals nationwide recover billions in lost revenue. By utilizing cutting-edge AI and machine learning, our client is transforming the way healthcare claims are processed, delivering smarter, faster, and more accurate systems. Be part of a forward-thinking team driving real impact in healthcare operations across the country.
Role Overview:
We are looking for a Senior Data Scientist to play a pivotal role in building and deploying advanced machine learning models that revolutionize healthcare claim processing. This role goes beyond traditional data science, requiring strong expertise in machine learning engineering (MLE), MLOps, and full-stack model development. You’ll work closely with both data scientists and engineers, engaging in the entire lifecycle of machine learning models—from design and deployment to optimization and scaling.
This is an exciting opportunity to tackle complex data challenges, contribute to mission-critical systems, and help drive operational efficiencies that directly enhance hospital revenue recovery.
What You’ll Do:
- Develop Full-Stack ML Solutions: Design, build, and deploy machine learning models that optimize healthcare claim workflows, focusing on recommendation systems and prioritization logic.
- ML Engineering & MLOps: Take ownership of end-to-end model development, from data preprocessing and feature engineering to deployment, monitoring, and iterative improvement using MLOps best practices.
- Work with Complex Data: Tackle unstructured and evolving datasets, ensuring models remain accurate and adaptable to changing client needs and new data.
- Collaborate Across Teams: Partner with engineers to integrate models into production environments and ensure they are scalable, reliable, and performant.
- Full Lifecycle Involvement: Engage in the full stack of machine learning—from conception and data exploration to deployment and operational monitoring—ensuring solutions are both innovative and practical.
What We’re Looking For:
- Experience: 5+ years in data science or machine learning, with a focus on full lifecycle machine learning engineering and complex data environments.
- ML Engineering & MLOps Skills: Proven experience with MLOps practices, building robust, scalable pipelines that monitor and maintain model health.
- Full-Stack Model Development: Expertise in model development and deployment, handling messy and evolving datasets, and working within industries with complex data such as insurance, fraud detection, e-commerce, or consulting.
- Problem Solving: A passion for driving continuous improvement in model performance and operational outcomes.
- Industry Background: Prior experience in healthcare is a plus but not required.
Why You Should Apply:
- Competitive Compensation: Earn up to $200,000 per year, plus a 10% performance bonus.
- Career Growth: Enjoy opportunities for professional development within a forward-thinking, innovative organization.
- Remote Flexibility: Work from anywhere in the United States while contributing to groundbreaking AI solutions.
Application Process:
- Initial interview with the hiring manager
- Technical screening
- Virtual onsite interviews
If you are a data scientist with a passion for applying full-stack machine learning to real-world challenges, we’d love to hear from you. Apply now to join a team that’s transforming healthcare through advanced AI and machine learning solutions.
