I'm a dedicated data scientist with a deep passion for leveraging data to drive insightful decisions. Holding a recently completed Master's degree in Data Science and backed by three years of hands-on experience, I am committed to contributing innovative solutions in the field. My role as a data scientist intern at the Metropolitan Transportation Commission has granted me firsthand exposure to the transformative power of data-driven strategies. My expertise is centered around deep learning, NLP, and computer vision, and I am enthusiastic about applying these skills to tangible challenges.
I'm a US Citizen and open to W2, contract, full-time work, as well as relocation opportunities.
Welcome to my online portfolio, where you can delve into a comprehensive exploration of my skills, experience, and passions. Take a closer look at my expertise, journey, and interests in the dynamic realm of data science. Whether you're seeking potential collaborations or exploring exciting opportunities, this platform is your gateway to connect and engage. Let's embark on a meaningful dialogue and explore the possibilities together.
Led a comprehensive geospatial initiative, curating zoning data for over 100 jurisdictions and 8 unincorporated regions via GeoJSON maps, optimizing workflows, and achieving time savings for a dedicated team. Pioneered a Computer Vision endeavor, enhancing a predictive model through advanced techniques, raising the F1 score by .05, while showcasing proficiency in tools such as AWS, GeoPandas, PyTorch, and Tableau. Additionally, conducted a Capacity Data Imputation Project, addressing missing values for critical features like max Density Units per Acre and Floor Area Ratio. This involved extracting capacity data, executing AWS Redshift SQL queries, and employing various data science techniques, including GeoPandas and Random Forest algorithms, for effective predictive imputation.
Guided workshops for 30 attendees each, covering business analytics and model metrics. Supported 8 students with coursework, from statistics to machine learning. Co-presented advanced ML insights in collaboration.
Led shifts for customer satisfaction, managed well-being of 8 employees, and optimized restaurant profits. Trained 20+ team members in diverse roles and consistently maintained a 92% satisfaction rate through 100+ monthly surveys.
Utilized specialized data collection software and mobile applications to ensure accurate and efficient data entry, contributing to the integrity of the United States Census database. Conducted in-depth interviews with a diverse range of respondents collecting and verifying crucial demographic, socioeconomic and geographic information
Relevant Coursework: Machine Learning, Linear Regression, Time Series Analysis, Programming (Python), Data Structures and Algorithms, Data Visualization, Data Analytics (PowerBI and Tableau), Data Acquisition, SQL, NoSQL, Distributed Computing (Spark), A/B Testing
Relevant Coursework: Linear Regression, Machine Learning, Advanced Statistics, Time Series Analysis, Programming in SAS, Data Science for Biology (Biometry)
Harnessing the Power of Artificial Intelligence with Microsoft Azure
Showcasing intermediate SQL querying skills
A comprehensive guide to effective IT troubleshooting, providing actionable tips to address common technical issues and ensure efficient operations.
Employed PyTorch and logistic regression on a diverse dataset, comprising a static JSON file with 883,636 reviews across 201,959 products and data from the Amazon API. Achieved robust sentiment prediction with a model yielding an impressive MAE.
Executed comprehensive linear regression modeling, featuring variance analysis, diagnostic checks for assumptions, and meticulous feature selection guided by BIC stepwise method.
Analyzed empathetic comments from GDELT data using DataBricks, leveraging Spark and Python to clean a massive GCP dataset, visualize geospatial patterns through scatter plots, and enhance processing speed through caching, showcasing adeptness in Spark and big data handling