hello, i'm niva.

I recently graduated from Northwestern University ('22), where I studied Computer Science and Statistics. I'm passionate about using algorithms and data ethically, thoughtfully, and for social good.

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‎‎‎‎‎‎‎‎./Skills

  • Frontend

    • proficient in React, JavaScript, HTML, CSS
    • working proficiency in TypeScript

  • Backend

    • proficient in Python (eg, Flask), Node.js, Express.js, REST APIs, SQL, NoSQL (eg, MongoDB)
    • working proficiency in Java, C, C++

  • Statistical

    • proficient in Python (pandas, scikit-learn, Seaborn, NumPy, Matplotlib), Excel
    • working proficiency in R, MATLAB, OpenRefine

  • Languages

    • fluent in English
    • working proficiency in Spanish, French, Hindi/Urdu

  • DevOps & Other

    • experience with Git, Amazon Web Services, Google Could Platform, Docker, Postman, Heroku, Unix

‎‎‎‎‎‎‎‎./Recent Experience

  • Full Stack Developer @ Unfound Jun 22 – Jan 23

    React • JavaScript • Node.js • Express.js • TypeScript • AWS • PostgreSQL • Docker
    • Designed and developed The Unfounder Sorter, a survey platform for connecting 20k+ users to crowd-sourced local gems.
    • Created recommendation algorithm and implemented sharing capabilities to optimize user experience and stickiness.
    • Built & maintained REST APIs; managed backend AWS processes with TypeScript, PostgreSQL, Node.js, and Express.js.

  • CS Peer Mentor @ Northwestern University Sep 21 – Mar 22

    MySQL • MongoDB • Python • Jupyter Notebook • pandas • NumPy • NLTK • scikit-learn • seaborn
    • Intro. to the Data Science Pipeline (COMP_SCI 396, 60+ students): Mentored students in data collection, cleaning, visualization, modeling, EDA, and statistical & machine learning techniques during weekly office hours.
    • Data Management and Information Processing (COMP_SCI 217, 60+ students): Mentored students in complex data set modeling and organization during weekly office hours.

  • Data Scientist, Program Coordinator, Tutor @ LumiNUs Tutors Apr 21 – Jan 22

    Excel • Python • pandas
    • Led program direction and analytics at LumiNUs Tutors, a volunteer tutoring organization that provides 1:1 mentorship to students of underserved Chicago Public Schools.
    • Conducted collection and analysis of learning and pedagogy data from 50+ students, 40+ tutors, and three data streams, including identification of program KPIs, survey development, statistical testing, and data visualizations.
    • Used data findings to improve program structure, materials, retention, marketing, and participant experience.
    • Remotely tutored a CPS high schooler on the SAT, building their core competencies and honing their test-taking strategies.

  • SAGE Edge Computing Intern @ Argonne National Laboratory Jun 21 – Aug 21

    Python • OpenCV
    • Developed plug-in for remote node network for comprehensive atmospheric tracking, modeling, and prediction in collaboration with climate scientists and other engineers.
    • Applied sparse and dense computer vision techniques to RADAR and LiDAR backscatter data plots to generate novel atmospheric insights.

  • Student Researcher @ LCAN Research Group Jan 19 – Mar 21

    Figma
    • Designed survey deployed to approximately 3,000 individuals to illuminate effects of COVID-19 pandemic on social isolation, technology use, healthcare, and health/wellness of older adult and neurodegenerative populations.
    • Tripled enrollment rate, streamlined recruitment methods, and liaised with participants of NIH-funded study to improve the design of a novel monitoring device (Rogers Research Group) and corresponding iPhone application (Figma) for those with Parkinson’s disease. Collected data from 15 study participants and analyzed data collected from this investigational system for device fidelity, user tolerance and acceptability, and digital biomarkers against gold-standard systems.
    • Co-authored paper accepted to the Conference on Motor Speech 2020 entitled “Evaluating a wearable mechano-acoustic sensor and iPhone application for speech data.”
    • Analyzed the speech of individuals with neurodegeneration at five levels of syntactic complexity with SALT (Systematic Analysis of Language Transcripts) and performed lexical error coding analysis with CLAN (Computerized Language ANalysis).