Data Scientist

I am a data scientist with experience applying machine learning and statistical analysis to business and engineering problems. I work comfortably with Python, SQL, AWS, and data visualization tools to turn complex datasets into practical insights.

My background combines data science, economics, mathematics, and computer science. I am currently pursuing an M.S. in Data Science & Analytics at Georgetown University, and I previously completed a B.A. in Economics & Mathematics with a minor in Computer Science at Boston University.

I have applied my skills in internship roles across both engineering and business settings. At Xiaomi Mobile Software Co., Ltd., I used machine learning, data cleaning, feature engineering, and classification modeling to automate engineering decision processes and improve accuracy significantly.

At Megalith Solutions LLC, I worked on lead-scoring and rule-based screening systems, collaborating with engineering and data teams to build scalable analytical workflows. I also contributed to a commercialized product that supported investor targeting and decision-making.

In addition to my internship experience, I have completed project work involving H-1B lottery analysis and Reddit workforce sentiment analysis. These projects strengthened my ability to perform exploratory analysis, build anomaly detection logic, and develop distributed data pipelines with PySpark and AWS.

I am especially interested in roles that combine analytics, machine learning, and business problem-solving. I enjoy building data-driven solutions that improve efficiency, support better decisions, and create measurable impact.