Nihar Atri

Aspiring Data Scientist/Software Engineer!

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About Me

Hi! I'm an incoming Master's student at Carnegie Mellon University, focusing on Data Science and Machine Learning through the Computational Data Science (MCDS) program. I recently graduated from Purdue University with a triple major in Computer Science, Data Science, and Applied Statistics. I am most interested in using Statistics and Machine Learning to generate insight into difficult and interdisciplinary problems. My professional experience spans across very diverse domains (from finance to agriculture), which has given me a deep appreciation for how adaptable and impactful data science and machine learning can be when applied thoughtfully.

Last summer, I worked as an Machine Learning Engineer Intern at a startup (Quantlink), where I built the core ELT pipelines and machine learning models that help investors make smarter financial decisisons. Before that, I worked as a Data Science intern at John Deere, building predictive models for machine failure, and a Software Engineer intern at Delta Airlines, where I developed an AWS-based content management platform for marketing teams.

At Purdue, I worked as an undergraduate researcher through several programs (DUIRI, VIP, and The Data Mine), exploring the intersection of machine learning/data science with medicine and political science, as well as conducting research in generative computer vision. I also enjoyed working as a Teaching Assistant for various courses, including Systems Programming, Data Engineering in Python, and Introduction to Data Science.

Besides my professional interests, I enjoy playing volleyball, tennis, piano, and drinking boba!

Technical Skills

  • Python
  • Java
  • SQL
  • C
  • Pandas
  • Scikit-learn
  • PySpark
  • TypeScript
  • AWS
  • LangChain
  • PyTorch
  • R
  • MongoDB
  • Dagster
  • Flask
  • Shell Scripting

Experience

Professional Experience

  1. Quantlink

    Machine Learning Engineer Intern

    Summer 2025

    • Designed core data pipelines with Dagster (orchestration/validation), dbt (transformation), and ClickHouse database to process 60M+ stock data points, enabling scalable data analysis

  2. Purdue Discovery Park

    Data Science Research Intern

    August 2024 — December 2024

    • Built a PyTorch sentiment analysis model to analyze public opinions on renewable energy/climate in the U.S.
    • Deployed the model as a Flask REST API in a Docker container to enable real-time predictions for political scientists
    • Created geospatial visualizations with GeoPandas; published results in the Purdue Journal of Undergraduate Research

  3. John Deere

    Data Science Intern

    Summer 2024

    • Developed a PySpark machine learning model pipeline that predicted farmer machine failure with 98% accuracy
    • Extracted & transformed data using SQL and fine-tuned Neural Network/Gradient Boosted classifiers on Databricks
    • Generated interactive dashboards with Plotly and Pandas to communicate findings to business stakeholders
    • Spearheaded a preemptive repair business model estimated to increase aftermarket recurring revenue by ~10%

  4. Purdue Low Power Computer Vision Lab

    Machine Learning Researcher

    January 2024 — May 2025

    • Implementing Diffusion and GAN architectures in PyTorch for embedded devices and comparing their efficiencies
    • Developed a YOLOv8 grading software that evaluates the accuracy and fidelity of generative image models
    • Deployed the grading software in the Low Power Computer Vision challenge to score teams' model submissions

  5. Delta Airlines

    Software Engineer Intern

    Summer 2023

    • Built an Angular site with TypeScript/Node.js backend to streamline asset management for marketing campaigns
    • Engineered the AWS architecture (Route 53, CloudSearch, Lambda functions, DynamoDB) in an Agile team
    • Automated CI/CD pipelines via GitLab and wrote unit tests with Jasmine, achieving 80% coverage

  6. ATOM Consortium (The Data Mine)

    Data Science Research Intern

    August 2022 — May 2023

    • Collaborated with pharmaceutical data scientists to accelerate drug discovery by predicting novel protein interactions
    • Conducted exploratory data analysis in Pandas and implemented Graph CNNs in PyTorch and Scikit-learn
    • Worked in an Agile setting with 5 interdisciplinary teammates and used Tableau to convey our results to researchers
    • Presented our findings at the Data Science Symposium to 400+ multidisciplinary students and researchers

Extracurricular Experience

  1. BoilerMake Hackathon

    Logistics Planning Member

    May 2022 — May 2025

    • Collaborated with 5 board members to contact 300+ companies and raise $110,000 for Purdue's largest hackathon
    • Leveraged strong interpersonal skills to negotiate with company representatives, resulting in a 15% funding increase
    • Boasted 500+ attendees and 15 corporate partnerships, with 96% of participants wanting to return

  2. Purdue LaunchPad

    Mentor

    August 2023 — May 2025

    • Mentoring freshman computer science students through developing programming projects
    • Communicating complex computer science concepts in simple terms and debugging code

  3. Machine Learning @ Purdue

    Club Member

    August 2023 — May 2025

    • Attended weekly meetings to discuss ML research papers and collaborate on projects

Teaching Experience

  1. Purdue University CS Department

    Undergraduate Teaching Assistant

    August 2023 — May 2025

    • Worked as a TA for CS 252: Systems Programming, CS 176: Data Engineering In Python, CS 242: Introduction to Data Science
    • Lead weekly help sessions (Practice/Study/Observation sessions) available to 900+ students, writing practice problems, and grading homeworks/exams
    • Host weekly office hours to help students review concepts and debug code

  2. The Data Mine

    Undergraduate Teaching Assistant

    August 2023 — May 2025

    • Helped develop and grade weekly homeworks on data science, data mining, and machine learning
    • Hosted weekly office hours/answered student questions on Piazza to help review concepts and debug code

  3. Kumon

    Math and Science Tutor

    Janurary 2019 – April 2019

    • Mentored ~20 middle to high school students in advanced math and science topics
    • Crafted effective curriculums based on the individual student's experience and age

Education

  1. Carnegie Mellon University

    Master of Computational Data Science

    2025 — 2026

    Specialized in Machine Learning
    GPA: 4.00

  2. Purdue University

    Bachelors of Science in CS, DS, and Applied Statistics

    2021 — 2025

    Tripled majored in Computer Science, Data Science, and Applied Statistics, specialized in Machine Intelligence
    GPA: 3.86

Relevant Coursework

Starred classes (*) indicate graduate courses

Machine Learning

  • *Introduction To Machine Learning
  • *Natural Language Processing
  • *Deep Learning
  • Artificial Intelligence
  • Data Mining

Computer Science

  • Analysis of Algorithms
  • Data Structures
  • Databases
  • Python Programming
  • Java Programming
  • C Programming

Data Science & Statistics

  • *Foundations of Data Science
  • Large Scale Data Analytics
  • Applied Regression Analysis
  • Time Series
  • Probability Theory
  • Statistical Inference

Mathematics

  • Linear Algebra
  • Multivariate Calculus
  • Discrete Mathematics

Projects

Project Image

Technologies & Tools

View on GitHub

Hobbies & Interests

Photography

Capturing moments through landscape and street photography. I love exploring the interplay of light and shadow, especially during golden hour shoots.

Music Production

Creating electronic music and beats in my home studio. I enjoy experimenting with different genres and sound design techniques using modern DAWs.

Rock Climbing

Indoor and outdoor climbing enthusiast. There's something about problem-solving on the wall that parallels the challenges I face in web development.

Game Development

Building indie games as a creative outlet. Currently working on a puzzle platformer using Unity and exploring procedural generation techniques.

Tech Reading

Staying current with emerging technologies and design trends. I regularly read industry publications and experiment with new frameworks and tools.

Travel

Exploring different cultures and architectures around the world. Travel inspires my design work and provides fresh perspectives on user experiences.

Contact

Get in Touch

Feel free to reach out for collaborations or just a friendly hello!

richard@example.com
+1 (213) 352-2795
Sacramento, California, USA

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