Yash Potdar
Yash Potdar
About Me ✌🏽
Welcome to my website! I’m Yash, a recent graduate from UC San Diego. This March, I graduated with highest honors (summa cum laude) while pursuing a double major in Data Science and Cognitive Science: Machine Learning.
I’m originally from San Ramon, CA (SF Bay Area 🌉). In my free time, I enjoy traveling, exploring new restaurants, cooking, and following/playing sports (go Niners and Warriors)!
One of my passions is teaching and mentorship. I served as an Instructional Assistant for several undergraduate data science courses and led workshops for students interested in data science. Check out my workshops!
I’m always looking to learn something new and connect with others! Feel free to contact me or connect on LinkedIn!
Work Experience 🧑🏽💻
Rivian ⚡ 🚙
Software Engineer Intern, Core Services
June 2022 – September 2022
- Architected and deployed a production-level service facilitating the settlement of vehicle transactions at scale.
- Improved the customer experience by streamlining internal communication pertaining to vehicle deliveries.
- Wrote documentation and wrote a tutorial to hand off my project to future developers, explain my design decisions, and identify areas of extension for other teams.
Halıcıoğlu Data Science Institute 📊 🧑🏽🏫
Data Science Instructional Assistant (IA)
September 2020 – March 2023
- Led 9 weekly discussion sections for a class of 120 undergraduate students, where I walked through challenging questions from the weekly programming assignment in order to solidify course concepts.
- Held weekly office hours to clarify Python and statistics concepts from lectures and guide students through programming assignments.
- Designed and created programming assignments and a final project to assess students’ understanding of course concepts.
- Served as an Instructional Assistant for DSC 10 5 times and for DSC 80 2 times.
HUGS (Startup) 🏡
Developer
May 2021 - June 2022
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Software Engineering Intern, R&D
March 2021 - May 2021
- Created wireframe prototypes and design language documents for the product, which is a housing portal that aims to bridge the gap between international students and landlords.
- Served as one of the initial Engineers and designed features for the housing platform.
LogicMonitor ☁️ 🤖
Data Science Intern, R&D
June 2021 - August 2021
- Researched and developed an early-stage feature on LogicMonitor’s platform for root cause analysis of alerts.
- Wrote a Confluence tutorial in order to explain to future developers the usage of the application, how I developed it, and areas of improvement so developers can continue working on the product.
University Organizations 🎓
Triton Consulting Group (TCG) 🕴️
VP Human Capital Management (HCM)
June 2022 - March 2023
- Planned social events, recruitment events, club retreats, study group sessions, and more to build a sense of community within TCG.
- Implemented strategies to foster a culture of inclusivity and increase retention within the organization.
Project Manager
October 2020 - June 2022
- Led the first iteration of a data analytics project for predicting churn using Machine Learning and analyzing ROI for a healthcare firm, which became a recurring client for TCG.
- Led a team of 5 Associates and worked directly with the CFO in order to successfully deliver a key project within scope, timeline, and budget.
- Conducted primary and secondary research and created a long-term marketing plan for UCSD’s Price Center.
Data Science Student Society (DS3) 📊
Professional Development Workshops Lead
June 2021 - September 2022
- Led the development of 2 workshops dedicated to career development for undergraduate members of the Data Science Student Society.
- Delivered workshops to prepare students for internship recruitment, such as resume reviews, networking sessions, or Leetcode workshops.
Kaggle Workshop Committee Member
June 2020 - June 2021
- Delivered 6 workshops on industry-relevant data science topics such as Pandas, Scikit-learn (sklearn) modeling, pipelines, and anomaly detection.
- Created content with the other Workshop Committee members in order to engage students interested in data science and enhance their learning.
ACM Cyber 🥷🏼 💻
Director of Finance & Logistics
July 2020 - June 2021
- Coordinated club events, which include workshops, networking events, seminars, and socials.
- Interfaced with other ACM Cyber Board members to seamlessly hold virtual events, due to the COVID-19 pandemic.
- Cultivated relationships with industry contacts for sponsors and mentors for organization members.
- Managed sponsorships and fundraising to ensure organization operations run smoothly.
- Secured funding to cover the expenditures from competition registration, event organization, and travel.
Projects 🧑🏽🍳
- Deep Learning for Pulmonary Edema Classification using Image Segmentation 🫁 🫀
- Trained multiple convolutional neural network (CNN) architectures in order to diagnose pulmonary edema from chest X-rays.
- Utilized transfer learning with a lung and heart image segmentation network in order to understand the impact of segmentation.
- Worked closely with a radiologist from UC San Diego Health for two quarters during this Data Science Senior Capstone project.
- Poster, Website, Paper
- Facebook Redesign 🧓🏽 #️⃣
- Conducted a UX case study for a Facebook redesign aimed to increase accessibility for the 65+ community and reduce sentiments of isolation and depression among this demographic.
- Interviewed members of the 65+ community in order to understand their core needs, pain points, and values.
- Designed high-fidelity and wireframe prototypes of the app redesign.
- Website
- Generating Sherlock Holmes Passages with Recurrent Neural Networks 🕵️♂️ 🗒️
- NYPD Police Complaint Classification Model 🚔
- Developed a DecisionTreeClassifier to predict whether civilian cases against officers in the New York Police Department were substantiated.
- Evaluated the parity of the classifier using the True Positive Parity measure to assess whether the model had systematic biases.
- Utilized scikit-learn transformers and pipelines to engineer features and develop the algorithm.
- Notebooks: Permutation Test, Classification ML Model
- MLB Pitch Classification ⚾
- Utilized supervised ML algorithms (Decision Trees and K-Nearest Neighbors) to solve the multi-label classification problem of classifying pitches as Changeups, Curveballs, Fastballs, or Sliders.
- Website
Teaching discussion! 🧑🏽🏫