PS: Used to be my old portfolio, but soon to be blog (dev notes). Stay tuned
I am a junior at Texas Tech University with strong problem-solving and communication skills, currently pursuing a Bachelor’s degree in Computer Science. Alongside my formal education, I actively explore the latest technologies and analytical methods to keep my skill set current. Upon graduating, I plan to apply these abilities to tackle complex technical problems in both software engineering and quantitative finance.
My interest in quantitative finance is driven by the challenge of leveraging computational and mathematical techniques to extract actionable insights from large, intricate datasets. I have been examining algorithmic trading concepts, data pipelines, and backtesting frameworks, with the goal of crafting robust, data-driven solutions that adapt to dynamic market conditions.
B.S., Computer Science | Texas Tech University - December 2026
Actively involved in:
Student Analyst I @ Texas Tech University - IT Help Central (Feb 2023 - Aug 2023)
- Served as first line technical support for departments, faculty, and students in the use of computing hardware, software, and network connections to facilitate access to IT services.
- Aided in the development and revision of 70+ technical knowledge base articles to help resolve reoccurring requests.
- Onboarded over 300 students and university staff in integrating Duo as the MFA medium for securing their accounts.
- Collaborated with 50+ senior staff & engineers to review and create new software solutions for the university
Cloud Engineer (mentee) @ BC Twenty (Aug 2023 - Dec 2024)
- Shadowed and collaborated with a team of five engineers on the design, development, and implementation of new software programs for clients.
- Regularly tested new implemented software features and provided detailed reports about any bugs or issues identified.
- Developed and optimized cloud architecture for web and mobile applications with senior staff.
- Experienced hands on implementation of multiple tools like Docker, Kubernetes, Ansible, etc.
Technical Interview Prep Fellow @ Codepath (Jun 2024 - Aug 2024)
- Collaborated with multiple pod members and solved 100+ algorithmic problems during breakout sessions
- Learned and adopted the use of UMPIRE method in solving technical problems from experienced software engineers
- Conducted 20+ mock interviews, while demonstrating a strong knowledge of DSA with over 85% ratings during the 10 weeks of the program
Undergraduate Campus Scout @ Collide Capital (Sep 2024 - Present)
- Interviewed and selected to join the Fall 2024 cohort after discovering and bringing a promising tech startup - Goalspaces - to the firm, leading the relationship-building efforts with the founders, positioning the firm for a potential series A investment
- Identified and vetted over 15 early-stage tech startups across various sectors, focusing on innovation, growth potential, and market disruption
- Designed a scalable research framework to evaluate startup viability, using data-driven analysis to assess product-market fit, team strength, and growth trajectory
- Currently acting as a liaison between the firm and founders, ensuring clear communication of investment criteria and fostering long-term, meaningful partnerships with a network of emerging tech innovators
Python – NumPy, Pandas, SciPy, Matplotlib , Seaborn, Yfinance
- Built a tool financial analysis tool, automating day-end stock data retrieval and visualizing metrics like volatility, skewness, and Sharpe Ratio
- Designed modular architecture for data fetching, statistical analysis, and visualization using NumPy, SciPy, Matplotlib, and Seaborn
- Created visual insights with returns distribution, volatility trends, and comparative stock statistics for portfolio analysis.
Python (Jupyter workspace, Pandas, NumPy, Matplotlib.pyplot, sklearn)
- Collaborated in a team of two to analyze the "Motor_Vehicle_Collisions_-_Crashes.csv" dataset, focusing on NYC vehicle accidents from 2016 to 2022.
- Filtered and cleaned the large dataset, reducing it from over a million records to approximately 154,000 records for more accurate analysis.
- Utilized Jupyter Python workspace and leveraged various libraries (e.g., pandas, NumPy, matplotlib) to develop and train a precise predictive model.
- Trained and visualized the model using multiple python libraries and achieved a RMSE of ~ 0.38%
- Conducted thorough data exploration and cleaning to ensure high-quality data for analysis and modeling.
- Presented findings and model results to the class, demonstrating a deep understanding of the dataset and the analytical techniques employed.
- Demonstrated strong teamwork and communication skills, coordinating effectively to meet project deadlines and deliver high-quality results.
Python,Typescript, Plaid API, Terraform, AWS API gateway, AWS Lambda, AWS DynamoDB
- Collaborated with team members to integrate backend services with the front-end interface, achieving seamless functionality.
- Implemented Lambda functions and APIs to support the core features of the application, ensuring efficient and reliable performance.
- Demonstrated proficiency in AWS services and cloud-based architecture, enhancing the scalability and flexibility of the application.
- Played a key role in debugging and troubleshooting issues, ensuring the app met project requirements and user expectations.
React.JS, Typescript, Python, FAST API, Pydantic, Docker
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Developed a web-based student management system enabling comprehensive management of student records, including adding, viewing, updating, and deleting information, increasing administrative efficiency by an estimated 40%.
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Employed React with TypeScript for type-safe development and Material-UI for responsive design, achieving a modern interface that enhanced user experience by approximately 30%. Integrated with FastAPI and SQLite for a high-performance backend that improved data access speed by 25%.
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Incorporated robust data validation and error handling, reducing data entry errors by an estimated 50%, ensuring the system’s reliability and data integrity.
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Created and documented five key API endpoints that allow seamless CRUD operations, facilitating a 20% faster workflow in student data management.
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Built with scalability in mind, with planned enhancements such as AWS DynamoDB integration and advanced features like user authentication and performance analytics projected to increase system capabilities by 35%.
Python backend, tkinter
- Built a monolithic local application for supermarket shopping.
- Created two levels of IAM users and their functions in the application.
- Implemented memory efficiency and least privilege access for various types of users in the simulation.
<more in progress, stay tuned...........>
Do not hesitate to reach out :)
Email: [email protected]
- New Horizons Institute - Python Development - 2021
- AWS Certified Cloud Practitioner — 2023
- AWS Certified Solutions Architect Professional — 2024 (in progress)
- Codepath Technical Interview Prep TIP101 — 2024