Hard Skills

- Predictive Modeling & Statistical Analysis

- Machine Learning (XGBoost, Random Forest, Deep Learning)

- Natural Language Processing (NLP) for Clinical Text

- Data Wrangling & ETL Pipelines

- Time Series Forecasting for Hospital Admissions

- Cloud Platforms (Azure Healthcare, AWS SageMaker)

- Data Visualization (Tableau, Power BI, Plotly Dash)

- Programming Languages: Python, R, SQL

- Healthcare Data Standards (HL7, FHIR, DICOM)

Soft Skills

- Critical Thinking & Problem Solving

- Cross-functional Collaboration

- Stakeholder Communication

- Agile Development Methodology

- Ethical Data Governance & Privacy Compliance

- Continuous Learning & Adaptability

*Senior Data Scientist*

*Boston Medical Analytics | Boston, MA*

June 2022 – Present

- Developed ML models to predict hospital readmission risks, leading to a 15% reduction in readmission rates through targeted intervention programs.

- Led NLP initiatives analyzing electronic health record (EHR) notes, extracting clinical entities to assist in early diagnosis of chronic conditions.

- Designed and implemented real-time dashboards in Tableau for clinical operations, enabling proactive resource management.

- Collaborated with data engineers to optimize ETL pipelines, improving data refresh cycle times by 35%.

*Healthcare Data Analyst & ML Engineer*

*MediCare Innovators | Boston, MA*

August 2018 – May 2022

- Built predictive models assessing patient mortality risk, integrating data from EHR, insurance claims, and wearable devices.

- Spearheaded an NLP project to classify unstructured clinical documentation, increasing coding accuracy by 20%.

- Conducted statistical analyses on large datasets to identify disparities in care delivery across demographic groups.

- Managed data governance processes ensuring compliance with HIPAA and GDPR standards.

*Data Analyst*

*HealthTech Solutions | Cambridge, MA*

June 2016 – July 2018

- Supported data-driven decision-making through robust reporting on patient flow and operational efficiency.

- Enhanced data collection methods from IoT-enabled devices, resulting in improved monitoring of patient vitals.

**Master of Science in Data Science**

Northeastern University, Boston, MA

2014 – 2016

**Bachelor of Science in Biomedical Engineering**

University of Massachusetts, Amherst, MA

2010 – 2014

- Certified Health Data Analyst (CHDA) – AHIMA

- AWS Certified Machine Learning – Specialty

- Clinical Data Science Certification – Stanford University (Coursera)

- **COVID-19 Hospitalization Prediction Model**: Developed a Bayesian time-series model integrating socio-economic and health data, achieving 88% accuracy in predicting peak hospitalization periods.

- **AI-Powered Patient Triage System**: Led a project deploying NLP algorithms to analyze triage notes, reducing wait times and improving diagnostic throughput by 12%.

- **Remote Patient Monitoring Dashboard**: Built an integrated dashboard aggregating wearable device data, providing clinicians real-time insights into patient health metrics.

- Python (Pandas, Scikit-Learn, TensorFlow, NLP libraries)

- R (Caret, Shiny)

- SQL & NoSQL Databases (PostgreSQL, MongoDB)

- Cloud Platforms: Amazon Web Services, Azure Healthcare Suite

- Visualization: Tableau, Power BI, Plotly Dash

- Healthcare Standards: HL7, FHIR, DICOM

- English (Native)

- Spanish (Professional Proficiency)