Salud Revenue Partners (Salud) is a technology-enabled service company with leadership and a high-performance culture that partners with healthcare providers nationwide to improve their revenue cycle performance.
Our vision is to be a national model for the delivery of revenue cycle services. We are at the forefront of innovation, applying next generation process automation and artificial intelligence to focus on the most productive work 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.
At Salud Revenue Partners, you can work for an organization dedicated to your employee development as well as delivering unparalleled results for our customers. We give staff objectives, exceptional training, and technology-enabled resources to accomplish goals and then set them free to get the job done. We encourage fresh ideas and a collaborative approach to delivering industry-leading solutions to clients.

What do our staff say about Salud? In May 2025 we were certified a Great Place to Work (for the 3rd year in a row), below are a few of our survey results:

• 97% of our employees say this is a great place to work!
• 97% of our staff say, “When you join the company, you are made to feel welcome.”
• 97% of our employees say, “When I look at what we accomplish, I feel a sense of pride.”
• 99% of our employees say, “People are encouraged to balance their work life and their personal life.”

QUALIFICATIONS

• Education: Master?s or PhD in a relevant field (Computer Science, Data Science, Machine Learning, Statistics, etc.) preferred.
• Experience: 5+ years of experience developing and deploying machine learning models, including both structured and unstructured data, from conception to production. Prior experience in a leadership capacity (such as tech lead, team lead, or project manager for data initiatives) is highly desired.
• Technical Skills: Expert in machine learning algorithms and statistical modeling techniques. Proficient in programming with Python (pandas, scikit-learn, TensorFlow/PyTorch) and SQL; familiarity with R or other languages is a bonus. Experience with data visualization tools and libraries to communicate data insights. Comfortable with big data technologies (e.g., Spark, Hadoop) and cloud ML services (AWS, GCP, or Azure ML stack) for scaling models. Experience with Azure ML specifically is a plus. Solid understanding of software engineering practices (version control, code reviews) and MLOps concepts for model deployment and lifecycle management.
• Analytical and Domain Skills: Demonstrated success in at least two of the following: predictive analytics, NLP, or recommendation systems. Strong grasp of experimental design, evaluation metrics, and the ability to validate model performance rigorously. Able to understand business domain context quickly; experience with healthcare data/claims or related domains is a plus, especially any experience dealing with similar data or predictive challenges.
• People Skills: Excellent leadership and project management skills ? capable of setting clear goals, meeting deadlines, and coordinating cross-functional efforts. Exceptional communication skills, with an ability to convey technical concepts to non-technical audiences effectively. Proven ability to collaborate with diverse teams and to influence without direct authority. Innovative and self-driven, with a passion for staying at the forefront of AI research and applying it to real-world problems.
• Location & Work Arrangement: 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.
  This job operates in a professional cubicle or home office environment where standard office equipment such as computer, phones, photocopiers, filing cabinets and fax machines are utilized. The noise level in the work environment is minimal.

This is a full time, exempt position.

• Supervisory Responsibility: This position has some supervisor responsibilities.
• Physical Demands: While performing the duties of this job, the individual is regularly required to stand, bend, kneel, sit, walk, and use hands to touch, type, handle, or feel objects; reach with hands and arms; talk and hear. The vision requirements include close vision, distance vision, color vision, peripheral vision, depth perception and the ability to adjust focus. Individual may occasionally lift and/or move up to 10 pounds.
• Travel: Travel when necessary for client work or training is expected for this position.

ROLE OVERVIEW:

We are seeking an experienced AI Strategic Leader to establish and lead our AI division, which will focus on high-impact solutions in predictive analytics, natural language processing (NLP), and recommendation systems. This is a strategic and hands-on leadership role, perfect for someone who thrives at the intersection of machine learning innovation and real-world implementation. You will shape the roadmap for AI at our organization, partner with our strong infrastructure, data engineering, and application teams, and build models that improve outcomes, personalize experiences, and drive smarter decision-making.

KEY RESPONSIBILITIES

• Strategy & Leadership: Act as the technical and strategic leader for the AI function. Partner with executive and operational stakeholders to identify use cases, define success criteria, and ensure that AI initiatives are aligned with organizational goals.
• Predictive Analytics Models: Lead the development of machine learning models that use structured data to perform classification, regression, forecasting, and risk prediction. These models will directly support operational performance, business planning, and decision support.
• NLP Capabilities: Design and implement NLP solutions including document classification, entity recognition, text summarization, and semantic analysis. These tools will help automate workflows, analyze large-scale communication data, and enhance user interaction.
• Recommendation Systems: Architect recommendation systems for personalization and next-best-action applications. You will work with collaborative filtering, content-based filtering, and hybrid models to enhance user experience and decision automation.
• Cross-Functional Integration: Collaborate closely with data engineering and software development teams to source, prepare, and manage structured and unstructured data. Ensure machine learning models are integrated securely and scalable into production environments through APIs or cloud platforms.
• Team Building & Mentorship: As the division grows, participate in hiring additional data scientists or ML engineers. Mentor team members and foster an environment of learning and innovation. Provide technical guidance and best practices in data science (coding standards, experimentation, documentation) to both the AI team and the wider organization?s analysts who might benefit from your expertise.
• Promote Research and Innovation: Stay current with academic and industry developments in AI. Evaluate and adapt new technologies, frameworks, and modeling techniques to keep the organization at the leading edge of applied machine learning.