👋Hello, I'm Yash Khadilkar!
Welcome to my Personal Portfolio! I'm a data scientist based out of San Francisco, CA. I studied Biomedical Engineering and Bioinformatics at UC Irvine and am currently pursuing an MS in Business Analytics at UCLA Anderson.
My experience spans data science, engineering, and research, with internships at Cepheid, Starboard Medical, and as a Data Scientist for NeuroDetect. I'm currently a Graduate Student Researcher at UCLA Anderson, working on optimization models for nonprofit fundraising strategies using linear programming and network flow algorithms.
I'm passionate about using data and strategic insights to drive innovation in big tech, consulting, biotech, and fintech companies.
Besides data science, I love talking about the NBA (especially the Golden State Warriors), the NFL (Niners), fantasy football, books, and hitting the gym.
Senior Capstone Project
Low-Cost, Efficient Microelectrode Array System
Position: Team Lead
Awards: UCI BioENGINE Industry Award, Chancellor’s Award for Excellence in Undergraduate Research, Undergraduate
Research Opportunities Program (UROP) Fellowship.
Led a team of 5 biomedical engineers to research and develop an award-winning microelectrode array recording system capable of recording neuronal voltage signals for the early diagnosis of neurological disorders.
Sprint Project
Redesigning Medium's Reading Experience
Led a five-day design sprint to tackle low session depth on Medium's web platform. Our team identified that users frequently exit after reading a single article due to weak feed trust and high decision friction. We designed a continuous reading flow with explicit binary feedback, lightweight social proof, and a proactive article selection overlay to help users confidently discover what to read next. Validated through user interviews with paid Medium subscribers and prototyped in Figma.
Data Science Projects
NBA Salary Optimization & Contract Efficiency Analysis
A machine learning-powered system that identifies market inefficiencies in NBA player contracts using predictive modeling and optimization algorithms. It analyzes 3,360+ player-seasons to generate roster construction strategies, trade recommendations, and contract valuations for front office decision-making.
Medical Device Regulation Navigator
An AI-powered system that helps navigate FDA medical device regulations using Retrieval-Augmented Generation (RAG). It answers questions about compliance requirements and approval pathways.
Global and Local Alignment Application
A comprehensive Python application for performing global and local sequence alignments using dynamic programming algorithms.
Certifications and Specialization
AWS Certified Machine Learning Engineer - Associate
The certification validates the ability to develop, deploy, and monitor production ML solutions on AWS, including data engineering, model implementation, performance optimization, and security best practices.
AWS Solutions Architect - Associate
The certification validates the ability to design secure, scalable, and resilient cloud architectures on AWS using best practices and customer-driven requirements.
AWS Cloud Practitioner
The certification validates basic understanding of AWS cloud concepts, services, security, architecture, pricing, and support.
Big Data Fundamentals with PySpark
This certification taught me the fundamentals of Big Data processing using PySpark, where I learned to work with Resilient Distributed Datasets (RDDs), Spark SQL DataFrames, and machine learning algorithms through hands-on projects analyzing Shakespeare's works, FIFA data, and genomic datasets. I gained practical experience with Apache Spark's distributed computing framework and built real applications like movie recommendation engines and spam filters using PySpark's powerful libraries.
Intermediate SQL
The certification taught me how to write SQL queries to extract, filter, and analyze data from databases, including using aggregate functions to calculate summaries and perform calculations that turn raw data into actionable insights. I also mastered sorting and grouping techniques to identify trends and patterns, giving me the skills to answer complex business questions through hands-on data analysis.
Introduction to Structured Query Language (SQL)
This certification taught me the fundamentals of SQL database language, covering basic syntax, multi-table database design, and essential operations like JOINs and foreign keys.
Data Structures and Algorithms Specialization
This specialization was designed to help me master fundamental algorithms and data structures to advance my career in software engineering or data science, with a strong focus on preparing for technical coding interviews at major tech companies.
Object-Oriented Data Structures in C++
This certification taught me how to program in C++ with a focus on implementing data structures as classes, including setting up a development environment for writing and debugging C++ code.
R Programming
This certification taught me how to program in R for statistical computing and data analysis, covering everything from installation and setup to writing functions, debugging, and organizing code. Also, I learned practical statistical programming skills through hands-on examples.
Six Sigma Foundations
This certification taught me how to apply Six Sigma methodology—a data-driven approach focused on improving processes, products, and services by reducing defects and variation. I learned the complete DMAIC framework (Define, Measure, Analyze, Improve, Control) along with key concepts like CTQ requirements, sigma levels, and project selection to successfully drive quality improvements in any organization.
Resume
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