Bridging Medicine & Machine Learning

Clinical Data Architect

Architecting predictive healthcare models and robust, HIPAA-compliant data pipelines to translate complex clinical ecosystems into life-saving, actionable insights.

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Professional Trajectory

Operational Impact

2020 — Present

Lead Clinical Data Scientist

NeuroTech Health Solutions
  • Architected and deployed a federated learning framework for cross-institutional neurological scan analysis, increasing predictive accuracy for early-onset Alzheimer's by 22%.
  • Engineered scalable ETL pipelines on AWS Healthcare cloud, processing over 50TB of raw genomic and EHR data with 99.9% uptime.
  • Reduced diagnostic latency by 40% through the implementation of an automated, AI-driven triage dashboard utilized by over 200 clinicians daily.
  • Mentored a cross-functional team of 6 junior data engineers and clinical analysts, bridging the gap between technical infrastructure and medical utility.
2017 — 2020

Health Informatics Architect

Global Care Partners
  • Spearheaded the unified integration of disparate Electronic Health Records (EHR) across 15 regional hospitals utilizing HL7 FHIR standards.
  • Developed a real-time patient risk stratification engine using Python and SQL, identifying high-risk readmission candidates within 24 hours of discharge.
  • Optimized legacy database queries by 60%, drastically reducing report generation times for hospital administrators.
2014 — 2017

Bioinformatics Researcher

Apex Medical Institute
  • Designed and validated statistical algorithms in R for early oncology detection based on biomarker variance arrays.
  • Co-authored 3 peer-reviewed papers on computational biology and predictive modeling in the Journal of Health Informatics.
  • Built internal data visualization tools utilized by laboratory technicians to monitor ongoing clinical trials.
Technical Competencies

Capabilities Radar

Data & AI Engineering

Python / PyTorch / TensorFlow 95%
Advanced SQL & NoSQL 90%
R / Statistical Modeling 85%

Healthcare Interoperability

HL7 FHIR & SMART on FHIR 95%
EHR/EMR API Integrations (Epic, Cerner) 88%
HIPAA / HITRUST Compliance Architecture 92%

Infrastructure & DevOps

AWS HealthLake / EC2 / S3 85%
Docker & Kubernetes 80%
CI/CD Pipelines (GitLab, Actions) 75%

Human-Centric Competencies

Cross-functional Clinical Communication
Ethical AI Advocacy
Evidence-Based Problem Solving
Agile Leadership
Patient-First Mentality
Degree

Ph.D. in Health Informatics

Stanford University • 2014
Degree

M.S. in Biostatistics

Johns Hopkins University • 2010
Certification

AWS Certified Data Analytics

Amazon Web Services • Active
Certification

CPHIMS Certified Professional

HIMSS • Active
Applied Research & Development

Clinical Case Studies

Abstract brain scan representation
PyTorch Computer Vision AWS

NeuroScan Federated Predictor

A federated learning model deployed across 4 distinct healthcare networks allowing decentralized training on MRI scans without migrating sensitive patient data. Resulted in a generalized model for early-stage tumor detection with 94% AUC.

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Code on a screen showing data algorithms
HL7 FHIR Node.js PostgreSQL

OmniCare Interoperability Gateway

Built a custom middleware solution that standardizes inbound CCDA documents into FHIR R4 resources. This enabled seamless data exchange between legacy outpatient clinics and a modern centralized hospital Epic EMR system.

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Data dashboard on a laptop
Python (Pandas) React D3.js

Sepsis Risk Stratification Engine

Developed an end-to-end real-time monitoring dashboard for ICU units. The engine analyzes vital signs and lab results every 15 minutes, alerting nursing staff of impending sepsis shock up to 6 hours before clinical manifestation.

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Abstract neural network graphic
NLP Transformers Spark

Clinical Notes Entity Extractor

Implemented a custom BERT-based Natural Language Processing pipeline to extract unstructured ICD-10 codes, medication dosages, and patient sentiments from raw physician narrative notes, automating billing workflows.

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Professional Endorsements

Peer Validation

"Elias has a rare ability to translate complex clinical needs into highly efficient, scalable technical architectures. His work on our predictive models directly improved our ICU patient outcomes."

Dr. Sarah Jenkins Chief Medical Information Officer, Global Care Partners

"I've worked with many data scientists, but Elias's deep understanding of healthcare compliance and FHIR standards sets him apart. He builds pipelines that are not just fast, but impenetrable."

Marcus Thorne VP of Engineering, NeuroTech

"A true visionary in bioinformatics. Elias led our research team with agile methodologies previously unheard of in academic settings, delivering our oncology algorithms months ahead of schedule."

Dr. Aris Vlahos Lead Oncology Researcher, Apex Institute
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Let's Engineer the Future of Health.

Currently available for freelance consulting, advisory roles, or full-time senior mission engagements in health tech.

elias.vance@securehealth.io
Remote / Boston, MA
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