Data Scientist

Job DescriptionJob Description

Division/Department: IT

Location: Middleburg Heights, OH

Summary:

Quadax, an award-winning leader in healthcare revenue cycle technology, is seeking a Data Scientist to join our Team and help us create the best Revenue Cycle Optimization solution in the industry. You’ll use your knowledge of healthcare revenue cycle business objectives to identify necessary data (SQL, Excel, Snowflake), apply appropriate analytics (BI tools, Azure Foundry) and derive strategic insights to achieve the desired business benefits. You’ll work closely with product managers, other data scientists, engineers, and business analysts to ensure clear definition of all requirements and translating them into value. You’ll leverage data insights to optimize the revenue cycle product design and user experience of our Platform. We use PowerBI for visualization, Snowflake for data management & sharing, and Azure Foundry for all modeling. Local candidates . If necessary, open to candidates ONLY in: OH, PA, MI, IN, KY, WV, WI, AL TN, GA, FL, TX, MO, SD, NC. Visa sponsorship not available.

Responsibilities:

· Design, develop, validate, and deploy various model types that can be operationalized into Quadax products and client-facing solutions.

· Partner with Product Management and business stakeholders to identify high-value opportunities where data science, machine learning, and AI can improve healthcare revenue cycle outcomes (e.g., denials avoidance, payment optimization, eligibility prediction).

· Translate complex data analysis into clear, actionable insights and communicate results effectively to business leaders, product teams, and clients.

· Work with Development teams through SDLC to integrate models into production environments, ensuring scalability, reliability, and measurable business impact.

· Act as a thought leader and advocate for AI/ML adoption within Quadax—educating stakeholders on use cases, model performance, and industry best practices.

· Stay current on emerging AI/ML techniques, tools, and healthcare applications, bringing innovative ideas that align with Quadax’s mission and product strategy.

· Contribute to the development of reusable modeling frameworks, best practices, and documentation to accelerate future data science initiatives.

· Ensure compliance with healthcare data privacy and security standards (HIPAA, HITRUST) in all modeling and data-handling activities.

Qualifications:

· Healthcare domain expertise: Experience with healthcare revenue cycle management (RCM), payer/provider data, claims, remittance, denials, or related healthcare delivery organizations.

· Professional experience: 3–5 years of experience in Data Science or advanced analytics, with prior experience as a Data Science Analyst or equivalent.

· Programming & tools: Proficiency in Python for statistical analysis, machine learning, and data wrangling; strong SQL skills for querying and transforming healthcare data.

· Data platforms & BI: Experience working with BI/reporting environments and data warehouses (Snowflake, Power BI, Azure Synapse, etc.), including building reusable data pipelines and dashboards.

· Modeling & analytics: Demonstrated ability to build, validate, and deploy predictive/statistical models (e.g., regression, classification, clustering, forecasting) to solve business problems in healthcare operations.

· SDLC: Familiarity with agile methodologies, version control , and model lifecycle management.

· Process & requirements: Skilled at translating business needs into analytical requirements, developing process flow diagrams, and documenting data mapping.

· Business acumen: Strong understanding of how data science drives financial and operational outcomes in the healthcare revenue cycle. Ability to identify customer needs, evaluate available solutions, and propose data-driven approaches.

· Communication & storytelling: Strong written and verbal communication skills, with the ability to explain statistical results, financial impacts, and modeling assumptions to both technical and non-technical stakeholders.

· Collaboration: Experience working cross-functionally with Data Science Analysts, Engineers, and Product Managers to deliver scalable solutions.