Professional Summary
Senior data scientist driving generative AI adoption in healthcare with 5+ years shipping production ML systems for prior authorization, HEDIS quality measures, HCC risk adjustment, and member analytics. Delivered $300K+ in documented cost savings through AI automation, earning board and C-suite visibility. Expert in rapid prototyping within enterprise architecture, governance, and HIPAA regulatory constraints. Open-source contributor building tools to improve healthcare transparency and interoperability.
Experience
Senior Data Scientist
Leading GenAI initiatives in healthcare, specializing in prior authorization automation and AI governance.
Key Achievements:
- •Architected HEDIS quality measure evidence recommendation system using RAG, gaining executive visibility and currently in production deployment with cross-functional architecture teams.
- •Engineered HCC AI pipeline automating clinical evidence extraction and risk score validation, generating an estimated $300K+ in annual cost savings and earning a company spot award for innovation impact.
- •Led enterprise generative AI initiative in prior authorization workflows, iterating from initial prototype to production-ready urgent request triage system with LLM-driven clinical summarization, reducing turnaround from days to seconds.
- •Advised AI governance committee on policy, bias mitigation, and ethical AI adoption in healthcare workflows as part of the internal AI Center of Excellence.
- •Built generative AI automations for customer service and internal survey analysis, reducing processing time from one week to minutes.
- •Managed annual wellness visit outreach model, coordinating engagement with 30k+ members.
Technologies & Skills:
Data Scientist
Spearheaded GenAI development and predictive modeling for healthcare applications.
Key Achievements:
- •Spearheaded internal generative AI tool to answer company policy questions, streamlining knowledge retrieval across the organization.
- •Designed predictive model for medication non-adherence (presented at ISPOR 2023) and led outreach to 1,500 Medicare members, increasing engagement.
- •Partnered cross-functionally to deploy predictive models into production environments on Azure.
Technologies & Skills:
Associate Data Scientist
Developed risk models and optimized data pipelines for healthcare analytics.
Key Achievements:
- •Engineered risk driver model to interpret parameters from a large-scale internal risk engine.
- •Migrated legacy scikit-learn models to PySpark pipelines for scalable deployment in Azure Databricks.
Technologies & Skills:
Graduate Teaching Assistant
Supported students in Operating Systems coursework.
Key Achievements:
- •Instructed and mentored 150+ students per semester in operating systems concepts and labs.
Technologies & Skills:
Healthcare Informatics Intern
Developed web feedback analysis tools using topic modeling and sentiment analysis.
Key Achievements:
- •Created web feedback analysis tool using topic modeling and sentiment analysis to summarize thousands of customer surveys, presented results in a PowerBI dashboard
Technologies & Skills:
Undergraduate Research Assistant
Implemented LSTM models for video motion prediction.
Key Achievements:
- •Implemented LSTM model for motion prediction in video; co-authored paper accepted at IJCNN 2018.
Technologies & Skills:
Skills & Technologies
Data & Analytics
Machine Learning & AI
Cloud & Infrastructure
Tools & Others
Education
University of Louisiana at Lafayette
Lafayette, LA - Aug 2015 - May 2020
- M.S. in Computer Science | GPA: 4.0 | May 2020
- B.S. in Computer Science, Math Minor | GPA: 3.78 | Dec 2019 (graduated early)
Publications
Predicting Medication Non-Adherence Using Blue Cross Blue Shield of Louisiana's Historical Medical Claims
Kirby Z, Holloway J, Liu M, Ouyang J, Vicidomina B, Nigam S
ISPOR 2023
View publicationTraining Spiking ConvNets by STDP and Gradient Descent
Tavanaei A, Kirby Z, Maida A
IJCNN 2018
View publication