Hi, I’m Rachael Burris, an AI and machine learning leader with 5+ years of experience designing and deploying data-driven systems in health care. I’ve built scalable data infrastructure, clinical NLP pipelines, and cloud-based ML workflows that power production AI. I have proven expertise in transformer-based models (BERT, GPT), medical data standards (CDISC, SNOMED CT), and compliant cloud platforms (Azure). I translate clinical and real-world data into production AI while ensuring ethical, secure, and scalable deployment in regulated health care environments. I collaborate with pharma, CROs, and academic partners to deliver responsible AI solutions that meet regulatory and real-world evidence requirements.

Rachael Burris

Hi, I’m Rachael Burris, an AI and machine learning leader with 5+ years of experience designing and deploying data-driven systems in health care. I’ve built scalable data infrastructure, clinical NLP pipelines, and cloud-based ML workflows that power production AI. I have proven expertise in transformer-based models (BERT, GPT), medical data standards (CDISC, SNOMED CT), and compliant cloud platforms (Azure). I translate clinical and real-world data into production AI while ensuring ethical, secure, and scalable deployment in regulated health care environments. I collaborate with pharma, CROs, and academic partners to deliver responsible AI solutions that meet regulatory and real-world evidence requirements.

Available to hire

Hi, I’m Rachael Burris, an AI and machine learning leader with 5+ years of experience designing and deploying data-driven systems in health care. I’ve built scalable data infrastructure, clinical NLP pipelines, and cloud-based ML workflows that power production AI.

I have proven expertise in transformer-based models (BERT, GPT), medical data standards (CDISC, SNOMED CT), and compliant cloud platforms (Azure). I translate clinical and real-world data into production AI while ensuring ethical, secure, and scalable deployment in regulated health care environments. I collaborate with pharma, CROs, and academic partners to deliver responsible AI solutions that meet regulatory and real-world evidence requirements.

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Language

English
Fluent

Work Experience

Director of Data Analytics at Muscular Dystrophy Association
January 1, 2020 - September 1, 2025
Led the organization-wide AI initiative roadmap, deploying transformer-based models (BERT, GPT) for clinical NLP tasks including entity extraction, classification, and sentiment analysis. Designed scalable production ML workflows and maintained governance across data pipelines. Built standardized, model-ready medical datasets aligned to CDISC, SNOMED CT, and ICD-10 to enable reproducible analytics at scale. Oversaw cloud-based model deployment and lifecycle management in regulated healthcare environments, ensuring compliance with GDPR/HIPAA/GCP standards and robust monitoring. Partnered with pharma, CROs, and academic teams to align AI outputs with regulatory and real-world evidence requirements using agile practices.
Teaching Assistant (Part Time) at University of Chicago
January 1, 2022 - January 1, 2023
Mentored graduate students on machine learning, health analytics, and reproducible ML workflows. Assisted with course logistics, graded assignments, and contributed to student projects involving healthcare data and ML experiments.
Program Manager, Director at Muscular Dystrophy Association
January 1, 2018 - January 1, 2020
Led foundational data collection initiatives across 80+ sites. Ensured data quality and governance while maintaining regulatory compliance (GCP, HIPAA). Partnered with vendors to improve data standardization and analytics readiness.
Program Manager, Associate Director at Muscular Dystrophy Association
January 1, 2016 - January 1, 2018
Developed KPI dashboards to track clinical program performance and reporting accuracy. Coordinated with internal teams to ensure data completeness and regulatory compliance. Managed vendor partnerships to improve data standardization and analytic readiness.
Genetic Counseling Assistant at University of Washington Medical Center
January 1, 2015 - January 1, 2016
Conducted patient enrollment, collected family history, prepared pedigree charts, and created/maintained data entries for genetic diagnoses aligned to CDISC standards.

Education

Master of Science in Applied Data Science at University of Chicago
January 11, 2030 - January 20, 2026
Bachelor of Arts in Psychology at University of Washington
January 11, 2030 - January 20, 2026
Master of Science in Applied Data Science at University of Chicago
January 11, 2030 - January 20, 2026
Bachelor of Arts in Psychology at University of Washington
January 11, 2030 - January 20, 2026

Qualifications

Capstone Award for Best in Show
January 11, 2030 - January 20, 2026

Industry Experience

Healthcare, Life Sciences, Professional Services, Software & Internet