Hard Skills

- Clinical NLP & Text Mining

- Transformer-based Models (BERT, RoBERTa, Med-BERT)

- Named Entity Recognition (NER) & Entity Linking

- Healthcare Data Standards (HL7 FHIR, SNOMED CT, LOINC)

- Python, PyTorch, TensorFlow, Hugging Face

- Data Preprocessing & Annotation (spaCy, BRAT, Prodigy)

- Cloud Deployment (AWS, Azure)

- Docker and Kubernetes for scalable AI pipelines

Soft Skills

- Analytical Problem Solving

- Cross-functional Collaboration

- Healthcare Compliance & Data Privacy

- Continuous Learning & Adaptability

- Communicative & Presentation Skills

*Senior NLP Engineer | MedHealth AI Solutions, Boston, MA*

June 2022 – Present

- Led development of a clinical NLP platform that automated extraction of patient comorbidities, reducing manual chart review time by 60%.

- Developed domain-specific transformer models (Med-BERT) to improve accuracy in clinical note classification, achieving over 92% F1-score.

- Collaborated with healthcare providers to integrate NLP solutions with EHR systems, ensuring adherence to HIPAA and HL7 standards.

- Managed deployment of NLP models on AWS SageMaker, ensuring scalable and secure inference services.

NLP Data Scientist | HealthTech Innovate, Cambridge, MA

August 2019 – May 2022

- Built an NLP pipeline for patient symptom extraction from unstructured clinical notes using advanced NER techniques.

- Implemented a real-time question-answering system for clinical support, decreasing query response time by 40%.

- Conducted research on transformer models fine-tuned for medical abbreviations and jargon, significantly improving entity recognition in noisy texts.

- Enabled interoperability of NLP outputs with existing hospital information systems through HL7 FHIR protocol integration.

*Healthcare NLP Intern | BioMed Solutions, Boston, MA*

June 2018 – July 2019

- Assisted in annotating medical datasets for training NLP models focused on adverse drug event detection.

- Supported the deployment of a machine learning model that flagged high-risk prescriptions, leading to a pilot project in a local hospital.

**Master of Science in Computational Linguistics**

Northeastern University, Boston, MA — 2016-2018

**Bachelor of Science in Bioinformatics**

University of Massachusetts, Amherst, MA — 2012-2016

- Certified Healthcare AI Specialist (CHAIS) — 2024

- NLP with Deep Learning in PyTorch — Coursera, 2023

- AWS Certified Solutions Architect – Associate — 2022

- **MedNotes Annotator**: Developed a semi-automated annotation tool to speed up labeling of clinical notes, resulting in a 25% reduction in annotation time and improved model training efficiency.

- **COVID-19 Symptom Tracker**: Built an NLP pipeline to analyze social media and clinical records for early detection patterns, aiding public health monitoring.

- **Pharmacovigilance NER System**: Designed an NER model to identify adverse drug reactions in patient forums and clinical reports, contributing to predictive safety analytics.

- Python, PyTorch, TensorFlow, Hugging Face Transformers

- spaCy, scispaCy, Prodigy

- HL7 FHIR, SNOMED CT, LOINC

- Docker, Kubernetes, AWS (SageMaker, Lambda, EC2), Azure

- Git, Jenkins, CI/CD pipelines

- Python (Fluent)

- SQL (Intermediate)

- Bash (Intermediate)

**Note:** This resume is optimized for Applicant Tracking Systems by incorporating role-specific keywords, standard formatting, and relevant technical terminology to improve discoverability and match with healthcare NLP job descriptions.