
Recent Master’s graduate in Computer Science with a strong foundation in data structures, algorithms, and object-oriented programming using C, C++, Java, and Python. Experienced in building academic and team-based projects including a machine learning–based credit card fraud detection system and a full-stack web application developed in a hackathon setting. Skilled in problem-solving, software engineering principles, and writing clean, maintainable code. Motivated to apply technical skills to design and build scalable, high-quality software solutions while continuing to grow as a Software Development Engineer.
Programming Languages:
C, C, Java, Python
Data Structures & Algorithms:
Arrays, Linked Lists, Stacks, Queues, Hash Tables, Trees, Graphs, Heaps, Sorting & Searching Algorithms, Recursion, Dynamic Programming, Time & Space Complexity Analysis
Object-Oriented Programming:
Classes & Objects, Inheritance, Polymorphism, Encapsulation, Abstraction
Databases:
SQL, Relational Databases (MySQL/PostgreSQL), Basic NoSQL Concepts
Software Engineering:
SDLC, Agile Methodology, Version Control (Git), Debugging, Unit Testing, Code Reviews
Cloud & Distributed Systems:
REST APIs, Backend Development, Cloud Fundamentals (AWS EC2, S3), Microservices Concepts, Fault-Tolerant System Design
Machine Learning (Academic):
Supervised Learning, Data Preprocessing, Feature Engineering, Model Evaluation
SAS Programmer Intern — ProKlin T Inc, Seattle, WA
Jan 2024 – Present
• Analyze and preprocess clinical trial data using SAS to generate CDISC-compliant SDTM and ADaM datasets for regulatory submissions.
• Apply statistical and data mining techniques to transform raw EDC data into analysis-ready datasets and Tables, Figures, and Listings (TFLs) for regulatory submissions.
• Perform data validation and quality checks to ensure accuracy, consistency, and compliance with clinical data standards.
• Collaborate with cross-functional teams (statisticians and data managers) to support data review, documentation, and reporting processes.