Salud Revenue Partners (Salud) is looking to improve their revenue cycle performance by applying next generation process automation and artificial intelligence to help healthcare organizations resolve difficult accounts receivable, find gold in zero balance accounts, achieve the highest coding accuracy, and carry out patient-centered solutions to self-pay.
Requirements
- Proficient in Python, with experience using libraries such as scikit-learn, PyTorch, TensorFlow, and Hugging Face.
- Experience deploying models in production environments and working with tools like Docker, MLflow, or Airflow.
- 3-6 years of experience developing models in at least two of the following areas: structured prediction, NLP, or recommendation systems.
Responsibilities
- Deliver Predictive Modeling Solutions Build and tune machine learning models using structured data for use cases such as forecasting, classification, and risk scoring. These models will support decision-making, automation, and operational efficiency.
- Design NLP Models Develop NLP models for document classification, entity recognition, and semantic understanding using both traditional methods and modern deep learning architectures like transformers. Apply these solutions to optimize communication workflows and unstructured data analysis.
- Implement Recommendation Engines Build recommendation systems that support personalization and content ranking using collaborative filtering, content-based methods, and hybrid techniques. Help guide product or user decisions based on behavioral or contextual data.
- Collaborate on Data and Infrastructure Partner with data engineering to access, prepare, and pipeline structured and unstructured datasets. Contribute clean, testable code and participate in MLOps workflows including version control, containerization, and monitoring.
- Deploy and Monitor Models in Production Integrate machine learning models into software products or workflows. Monitor their performance and accuracy over time, manage retraining needs, and troubleshoot production issues as necessary.
- Document and Communicate Work Maintain clear documentation for models, datasets, and experiments. Share results with stakeholders and ensure reproducibility, transparency, and alignment with business goals.
Other
- Master’s or PhD in Data Science, Computer Science, Engineering, or a related field.
- Strong communication skills and ability to collaborate across technical and non-technical teams.
- We prefer candidates who can collaborate on-site with our team in West Lafayette, IN periodically.
- We support a hybrid work model, you’ll have flexibility to work from home part of the week while joining the team in person for key meetings, brainstorming sessions, and project kick-offs.
- Travel when necessary for client work or training may be needed periodically for this position.
