Data Science Analyst

Responsibilities:

• 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.

Qualifications:

• Healthcare revenue cycle experience with hospitals, providers, and/or other healthcare delivery organizations
• 2+ years of experience working as an IT Data Analyst or in Data Science
• Strong Python programming skills and experience with common ML frameworks (scikit-learn, XGBoost)
• Experience with agile development and software development life cycle (SDLC) processes
• Proficiency with SQL programming
• Experience with Microsoft Azure, including Azure AI/AI Foundry and related AI services
• Strong business acumen and data analysis skills and the ability to identify customer needs, analyze them against available solutions, and identify gaps
• Interprets and presents data analysis results including explanation of statistical and financial techniques used, assumptions made and summary of results
• Excellent written and verbal communication skills