Senior Data Scientist AI

About Ensemble Health Partners

Ensemble is a leading provider of technology-enabled revenue cycle management solutions for health systems, including hospitals and affiliated physician groups. They offer end-to-end revenue cycle solutions as well as a comprehensive suite of point solutions to clients across the country. Ensemble keeps communities healthy by keeping hospitals healthy. We recognize that healthcare requires a human touch, and we believe that every touch should be meaningful. This is why our people are the most important part of who we are. By empowering them to challenge the status quo, we know they will be the difference! O.N.E Purpose:

• Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations.
• Embracing New Ideas: Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation.
• Striving for Excellence: Execute at a high level by demonstrating our “Best in KLAS” Ensemble Difference Principles and consistently delivering outstanding results.

The Opportunity

Healthcare impacts each of us, yet the current system remains fundamentally broken. Many of us have seen loved ones face the devastating challenge of unaffordable care. At Ensemble, we are committed to changing this reality by driving down healthcare costs and eliminating obstacles, creating a system that truly puts people first, last, and always. We are dedicated to revolutionizing healthcare with cutting-edge, technology-enabled revenue cycle management solutions for health systems. We’re here to solve how to reduce the friction and improve the cost of healthcare for better client and patient outcomes. As a leader in revenue technology, Ensemble is redefining what is possible in healthcare through innovation, purpose and human-centered solutions. We offer end-to-end revenue cycle solutions as well as a comprehensive suite of point solutions to clients across the country. Why do we do what we do? It’s all about our O.N.E Purpose: Our commitment to transforming healthcare goes beyond technology and innovation. It’s rooted in a purpose-driven approach that emphasizes customer obsession, embraces new ideas, and strives for excellence—principles that define our O.N.E Purpose and inspire everything we do.

• Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations.
• Embracing New Ideas: Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation.
• Striving for Excellence: Execute at a high level by demonstrating our “Best in KLAS” Ensemble Difference Principles and consistently delivering outstanding results.

Job Summary

Take on a pivotal role in addressing healthcare’s toughest challenges with advanced AI solutions. As a Senior Data Scientist, you’ll build AI and Machine learning models and pipelines, with a focus on generative AI, LLMs and predictive modelling. Your work will enable hospitals and health systems to operate more efficiently and deliver better patient outcomes. The successful Senior Data Scientist candidate will work closely with business and product owners to understand their data requirements and product specification in order to help them make data-related decisions and product design choices. The role will also require close work with software engineers and developers to deliver solutions. The job role may also require you to learn new tools and technologies fast, which will be well supported by in-depth ML/AI knowledge as well as basic programming and scripting skills. You should have practical experience in the design, development, management, and maintenance of systems and handling of large datasets. You should have hands on experience with common machine learning and AI frameworks, and a good knowledge of AI and machine learning fundamentals (deep learning, regression, classification and clustering algorithms), retrieval augmented generation pipelines, as well as a good grasp of the design and evaluation of LLM-supported use cases.

Essential Job Functions

• Lead AI strategy by delivering solutions that combine software engineering, statistics, and machine learning effectively for complex clinical applications.
• Execute deep, thoughtful, analytical experiments that utilize the most appropriate techniques and lead to substantial incremental improvements.
• Deliver excellent reports and presentations to highlight relevant hypothesis and insights that drive decision making within the organization.
• Identify, collect, transform and explore data to become the resident expert on available data within the organization.
• Coordinate between Engineers and Product Analysts and the broader organization to facilitate seamless collaboration.

Other Preferred Knowledge, Skills And Abilities

• 3+ years experience working in data scientist capacity.
• PhD or MSc in Computer Science/Machine Learning/AI, or related work experience with the design, building and evaluation of Machine Learning systems.
• 3+ years’ experience with Machine Learning ecosystem tools, including pytorch/tensorflow, scikit-learn, xgboost or equivalents.
• Statistical Analysis: Proficiency in statistical techniques and tools.
• Machine Learning: Knowledge of machine learning algorithms and their applications.
• Programming: Strong programming skills (e.g., Python, R, or SQL).
• Data Visualization: Ability to create meaningful visualizations.
• Ability to design, implement, test and deploy Machine Learning models.
• Experience working with and evaluating LLM-based pipeline, with an emphasis on retrieval augmented generation and prompting techniques is a plus.
• Familiarity with langchain/llamaindex/haystack/Azure AI studio, vector databases and retrieval techniques, or equivalent common tools in the emerging LLM-enabled tech stack is a plus.
• Proficiency in accessing and handling databases via SQL, Azure Data Factory or similar.
• Alternatively, familiarity with data storage/management systems or Big Data frameworks (like Hadoop, Spark) expected to be known or used.
• Proficiency in Software Development best practices such as Continuous Integration, Unit/Integration Testing, Code Reviews.
• Understanding of MLOps fundamentals, including orchestration tools, cloud compute, and observability tools.
• Knowledge of Revenue Cycle Management, Collections, or financial industries is desirable but not necessary.
• Ability to work both independently and in a team-based, fast-paced environment.
• Excellent communication skills, both written and verbal.

Desired Work Experience

• 5 to 7 Years
• Must be inquisitive and demonstrate openness to innovation including AI to explore better processes and ways to alleviate friction and improve patient and client experiences.
• This is a remote position; however, candidates must be willing and able to travel to and work onsite at client, temporary, or corporate office locations as business needs require.

Desired Education

• Post Graduate Degree or Equivalent Experience

CAREER OPPORTUNITY OFFERING:

• Bonus Incentives
• Paid Certifications
• Tuition Reimbursement
• Comprehensive Benefits
• Career Advancement

This position pays between $83,200 - $159,450 based on experience.

Join An Award-winning Company

• Five-time winner of “Best in KLAS” 2020-2022, 2024-2025
• Black Book Research's Top Revenue Cycle Management Outsourcing Solution 2021-2024
• 22 Healthcare Financial Management Association (HFMA) MAP Awards for High Performance in Revenue Cycle 2019-2024
• Leader in Everest Group's RCM Operations PEAK Matrix Assessment 2024
• Clarivate Healthcare Business Insights (HBI) Revenue Cycle Awards for strong performance 2020, 2022-2023
• Energage Top Workplaces USA 2022-2024
• Fortune Media Best Workplaces in Healthcare 2024
• Monster Top Workplaces for Remote Work 2024
• Great Place to Work certified 2023-2024

Key skills/competency

• AI strategy
• Machine learning models
• Generative AI
• LLMs
• Predictive modeling
• Data analysis
• Software engineering
• Statistics
• Data visualization
• Problem-solving