Data Science Analyst

Summary: Quadax, an award-winning leader in healthcare revenue cycle technology, is seeking a Data Science Analyst 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 preferred.

Open to remote employees ONLY in: OH (if residence is outside a reasonably commutable distance), PA, MI, IN, KY, WV, WI, AL TN, GA, FL, TX, MO, SD, NC.

Ability to analyze complex data sets and create actionable insights Uses knowledge of business objectives, strategies, and needs to identify opportunities where data can be leveraged to achieve the desired business benefits Understands current data context, processes and availability, and how current data processes and existing data can be leveraged to achieve the desired benefits Prepares and analyzes data. This can include - locating, profiling, cleansing, extracting, mapping, importing, transforming, validating, or modeling Applies query, data exploration and transformation, basic statistical methods, and visualization techniques to create business insights or improve data quality Performs validation and testing to confirm the accuracy of the information created Design and develop AI/ML solutions using Azure AI services. Build and optimize document intelligence solutions using OCR, LLMs, and hybrid approaches. Support the creation and maintenance of project documentation Develop, train, and deploy machine learning models for production workloads.