Senior Machine Learning Engineer
About Revecore
Revecore is a leading provider of revenue integrity, underpayments solutions, denial prevention services, and complex claims solutions to U.S. health systems. Serving 1,200 hospital facilities across 42 states, we leverage a scalable operating platform powered by proprietary technology and decades of accumulated experience to improve the most complicated aspects of hospitals’ claims cycles. Our long-term vision is to evolve into an AI-enabled, best-in-class player that comprehensively addresses providers’ revenue optimization needs.
The Opportunity
We are seeking a Senior Machine Learning Engineer to join our team and drive our AI-enabled workflow program. In this role, you will leverage your expertise in machine learning, data analysis, and software engineering to enhance the productivity and efficiency of our underpayment business. You will have the opportunity to work on exciting projects, such as prioritizing claims based on expected recovery dollars, identifying root causes, and improving our claim-remit matching process. This is a great opportunity to contribute to the digital transformation of Revecore and make a significant impact on our business and the healthcare industry.
What You’ll Do
- Analyze and explore data to identify actionable opportunities from internal and 3rd party data.
- Own end-to-end development, training, productionization, evaluation, and improvement of machine learning systems to rank claim opportunities.
- Research, implement, and launch new model architectures that drive business impact.
- Continuously measure the impact of the AI-enabled workflows on key business metrics and use these measurements to improve the machine learning models and workflows.
- Partner and collaborate with cross-functional teams of software engineers, data engineers, subject matter experts, product managers and analysts to design and build practical solutions.
- Implement MLOps best practices to streamline the development, deployment, and maintenance of machine learning models.
What You’ll Bring
- Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field. A Master's degree or Ph.D. is preferred.
- Experience working in a similar role, with a focus on machine learning or data science.
- Experience, developing, and deploying machine learning models in a production environment. Experience with operating ML pipelines in a cloud platform (e.g., AWS, GCP, Azure)
- Ability to wrangle data, perform exploratory data analysis, and draw insights from visualizations.
- Applied experience with contemporary natural language processing (NLP) tasks, techniques, and tools (e.g., entity extraction, seq2seq modeling, transformers, hugging face).
- Experience with popular ML libraries/frameworks, such as scikit-learn, TensorFlow, PyTorch, in Python and/or Scala. Experience with Spark is a preferred.
- Excellent problem-solving skills, attention to detail, and ability to work effectively in a team.