During my data science internship at Millenium Management, I focused on analyzing market data to evaluate how economic indicators impacted futures. Using Python and Pandas, I conducted extensive data analysis, gathering, cleaning, and structuring data for visualizations with Matplotlib. This experience honed my Python skills and deepened my data-driven decision-making abilities.
I have a strong foundation in Python, with hands-on experience in data analysis and machine learning. During my internship at Millennium Management, I used Python, Pandas, and Matplotlib to manage and analyze extensive market data, identifying key volatility patterns linked to economic indicators and improving algorithmic trading strategies. My work involved rigorous data cleaning, structuring, and visualization, which enhanced my analytical abilities and taught me to derive actionable insights for strategic impact. Through my coursework, I further developed skills in Python programming, debugging, object-oriented design, and applied machine learning, using libraries like scikit-learn to implement data-driven solutions. Click hereto view some of my coursework from a python class.
In my applied machine learning and data mining course, I gained a solid foundation in essential machine learning algorithms and techniques, focusing on both supervised and unsupervised learning. Click here to see some of my ML experience. I developed practical skills in regression analysis, decision trees, and dimensionality reduction, along with resampling methods like cross-validation and bootstrap for model validation. Additionally, I explored clustering, kernel methods, and regularization to enhance model performance, and delved into deep learning, specifically with feedforward neural networks. This course also introduced me to scalable data processing with MapReduce, association rule mining, and recommender systems, equipping me with a strong analytical toolkit applicable to real-world data science challenges.
With a strong background in SQL, I've gained hands-on expertise in database design, querying, and data management. In my coursework, I developed data models, managed relational databases, and navigated complex data environments using SQL to retrieve, update, and organize information. My experience in both data management and full stack development enhanced my skills in relational database management, big-data analytics, and data integration across front-end and back-end interfaces. This foundation has provided me with a deep understanding of SQL’s role in data organization and retrieval for effective decision-making.
In the Learning and Forgetting in Neural Networks Lab, I researched federated learning, examining the impact of non-independent client data on model weight updates. This role strengthened my Python skills and introduced me to experimental design, iterative testing, and collaborative research in machine learning. Click here to learn more about the research
At TeraThought, I worked as a UI and UX designer on Shareful, a technology-driven project aimed at fostering sustainable resource sharing within communities. Leveraging tools like Figma and Miro, I collaborated in agile, 2-week sprints to create data-informed design solutions that enhanced user experience and established a robust foundation for the development team. Working in a startup environment sharpened my data-driven design skills, reinforced the importance of iterative feedback, and taught me how to integrate diverse ideas within cross-functional teams. This experience gave me a strong foundation in collaboration, adaptability, and the intricacies of building meaningful, scalable solutions from the ground up.
Click here to view certifications.
In DataCamp’s Intro to SQL course, I learned to extract and organize data using SQL queries and best practices. I gained hands-on experience with popular SQL variants like PostgreSQL and SQL Server, providing a solid foundation to apply SQL to data projects.
In completing DataCamp’s Intro to Power BI course, I learned how to create interactive, visually impactful reports from scratch. Through hands-on projects, I developed skills in data loading, transformation with Power Query, and building data models.
In DataCamp’s Intro to Excel course, I learned essential skills for data analysis, including data preparation, managing tables, and applying functions for calculations. I also explored creating visuals, like area, column, and pie charts, to effectively communicate insights.
As part of GRIDS (Graduates Rising in Data Science), I initially served as a marketing leader, where I grew the organization’s visibility by managing social media outreach and designing targeted advertisements. Later, I joined the web development team, leading the design, coding, and implementation of an advanced website to elevate GRIDS’ digital footprint and member engagement. By building new wireframes and optimizing the user interface, I enhanced the site’s functionality, contributing to a more interactive and data-informed user experience. Click here to see the website that I designed and implemented. This experience strengthened my skills in front-end development, data-driven design, and the integration of user-centered updates.
At Code Ninja, I mentored young students in coding projects, refining my skills in teaching complex technical concepts by breaking them into simpler steps—an invaluable skill in data science and problem-solving.