AI/ML Solutions Analyst

VieMed Careers•Lafayette, LA

About The Position

Essential Duties and Responsibilities: Data Preparation & Exploration Collect, clean, and preprocess patient, claims, billing, and operational data from healthcare systems (EHRs, billing platforms, CRM, etc.). Conduct exploratory data analysis (EDA) on datasets related to ventilator compliance, hospital readmissions, referral patterns, and payer trends. Modeling & Analysis Assist in building predictive and machine learning models (e.g., patient risk stratification, adherence prediction, referral conversion). Perform statistical and trend analysis to identify cost-saving opportunities and clinical/operational efficiencies. AI & Automation Development Support the design and prototyping of AI agents for tasks such as real-time eligibility checks, referral triage, and payer communication. Help build automated workflows and data pipelines that reduce manual processes (e.g., invoice/PO/receiving 3-way match, claims variance detection). Contribute to the development of chatbots and copilots that assist employees with data lookups, reporting, or documentation. Experiment with workflow automation tools and APIs to connect platforms such as Bonafide, Brightree, Acumatica, Salesforce, and Power Apps. Visualization & Communication Create dashboards and reports (Tableau/Power BI) that monitor patient outcomes, operational KPIs, and AI automation performance. Communicate results in clear, actionable terms for clinicians, operations staff, and executives. Collaboration & Support Work with data engineers to optimize data pipelines supporting AI/ML and automation initiatives.

Requirements

Bachelor’s degree in Data Science, Computer Science, Healthcare Informatics, or related field (Master’s a plus), or equivalent experience
Proficiency in Python (Pandas, NumPy, scikit-learn, LangChain, or similar frameworks for AI/agents).
Strong SQL skills for working with healthcare and operational data.
Familiarity with AI concepts such as LLMs, prompt engineering, and workflow orchestration.
Understanding of healthcare data (claims, EHR, payer data) and compliance standards (HIPAA).
Experience with data visualization tools (Tableau, Power BI, matplotlib, seaborn).
Strong problem-solving and communication skills.

Nice To Haves

Exposure to DME workflows (referrals, authorizations, billing, compliance).
Experience building AI-driven tools or copilots in Microsoft Copilot, ChatGPT Enterprise, or similar platforms.
Familiarity with workflow automation tools (Power Automate, Zapier, UiPath, etc.).
Cloud platform experience (AWS, Azure, or GCP).
Git/version control and collaborative development experience.

Responsibilities

Data Preparation & Exploration Collect, clean, and preprocess patient, claims, billing, and operational data from healthcare systems (EHRs, billing platforms, CRM, etc.).
Conduct exploratory data analysis (EDA) on datasets related to ventilator compliance, hospital readmissions, referral patterns, and payer trends.
Modeling & Analysis Assist in building predictive and machine learning models (e.g., patient risk stratification, adherence prediction, referral conversion).
Perform statistical and trend analysis to identify cost-saving opportunities and clinical/operational efficiencies.
AI & Automation Development Support the design and prototyping of AI agents for tasks such as real-time eligibility checks, referral triage, and payer communication.
Help build automated workflows and data pipelines that reduce manual processes (e.g., invoice/PO/receiving 3-way match, claims variance detection).
Contribute to the development of chatbots and copilots that assist employees with data lookups, reporting, or documentation.
Experiment with workflow automation tools and APIs to connect platforms such as Bonafide, Brightree, Acumatica, Salesforce, and Power Apps.
Visualization & Communication Create dashboards and reports (Tableau/Power BI) that monitor patient outcomes, operational KPIs, and AI automation performance.
Communicate results in clear, actionable terms for clinicians, operations staff, and executives.
Collaboration & Support Work with data engineers to optimize data pipelines supporting AI/ML and automation initiatives.