I’m Ishan Saksena, a data scientist-in-the-making fueled by curiosity, creativity, and a deep commitment to social good. For me, data isn’t just a collection of numbers; it’s a canvas for uncovering patterns, telling stories, and driving meaningful change. I thrive at the intersection of logic and imagination, where problems become opportunities for innovation. Outside of my love for data, I’m an advocate for animal welfare and a passionate storyteller. Whether I’m crafting compelling narratives or working on machine learning solutions, I believe in the power of ideas—big and small—to connect, inspire, and make a lasting impact.
Led a section of 25 students for SI330 Data Manipulation under Dr. Sabina Tomkins. Created assignments, midterms, and exams, conducted office hours, and led a team of Instructional Aides to support student success.
Analyzed 100+ million public transit records in the Puget Sound Area using PostgreSQL, Python, and R to extract insights on rider behavior and transit equity. Developed a data-driven scoring mechanism for King County Metro to prioritize bus shelter placement in underserved areas, integrating transfer and reduced fare card data. Created geospatial maps with PostGIS detailing transfer hotspots for Transit Agencies to improve service planning. Presented findings to King County, opening future research opportunities.
Spearheaded prompt engineering efforts using Amazon Bedrock to evaluate the performance of LLMs like GPT, Mixtral, Claude, and Titan. Achieved 50% cost savings by fine-tuning lower-tier models, eliminating expensive alternatives. Developed SQL scripts to enable data-driven business decisions and built analytics dashboards for monitoring user health and targeted campaigns.
Developed a real-time hybrid movie recommendation system using the Neo4j Graph database, which is being put into production. Researched methods to enhance user engagement through personalized content based on social connections and user preferences. Deployed the model to a web application using Python Flask, HTML, and CSS for personalized recommendations.
Outstanding Masters in Data Science Student Award 2024
GPA: 4.0
Hall of Fame 2023
Rank 1 – Semester 5, 6
GPA: 9.50/10