Currently an Extern @Beats By Dre·🟢 Open to work
I'm a software engineering graduate student ready to leverage data analytics for impactful product development.
Dive into my portfolio showcasing data-driven projects that blend qualitative and quantitative analysis in product development.
Beats By Dre · ✅ Verified by Extern · ⏱️ In progress
A Beats by Dre externship focused on extracting consumer insights from reviews and survey data using qualitative and quantitative analysis.
I'm a software engineering graduate student ready to leverage data analytics for impactful product development.
I am a graduate student pursuing a Master's Degree in Software Engineering, with a focus on product development. After taking a break, I am reentering the workforce and eager to enhance my skills and competitiveness in the tech industry.
Externships
Beats by Dre Data Analytics: Qualitative & Quantitative Insights
Beats By Dre
Experience
Part-Time Faculty, Design & Technology
The New School – Parsons School of Design, New York, NY · Jan 2023 – Present
Data Analytics Externship — Beats by Dre Project
Extern, Inc., New York, NY (Remote) · Nov 2025 – Feb 2026
Chief of Staff (Freelance)
Mentor Me Collective, Remote · Dec 2024 – Apr 2025
Project Management Track Lead (Volunteer)
Grow With Google, Remote · Aug 2024 – Nov 2024
Project Manager / Partnership & Impact Manager
Center for Tech and Civic Life, Chicago, IL (Remote) · Sep 2020 – Dec 2023
Research Resident
NYU – Interactive Telecommunications Program, New York, NY · Aug 2019 – Aug 2020
Junior Developer
Ventech Solutions, Columbus, OH · Jan 2016 – Aug 2017
Education
University of Maryland Global Campus
MS, Information Technology — Software Engineering · Class of 2026
New York University
MPS, Interactive Telecommunications Program · Class of 2019
Kent State University
BS, Technology · Class of 2003
Skills
✅ Verified by Extern · ⏱️ In progress
A Beats by Dre externship focused on extracting consumer insights from reviews and survey data using qualitative and quantitative analysis.
The work analyzed customer feedback and survey responses for Beats audio products, combining AI-assisted review coding with spreadsheet-based quantitative analysis. Deliverables included a pain-point taxonomy exported as JSON with category counts, an AIDA-format customer journey map listing actions, thoughts, emotions, and touchpoints, and cleaned survey data with summary statistics and
I produced a JSON-coded pain-point taxonomy with category counts, an AIDA customer journey map documenting actions and touchpoints, and a cleaned survey dataset with calculated means, medians, modes, correlations, and segment counts.
I analyzed 100+ user reviews with AI, extracted five pain-point clusters, converted results to JSON, and recorded counts per category. The output listed Microphone & Call Quality (22), Comfort & Fit (20), Battery Life & Charging (18), Bluetooth Connectivity & Controls (17), Sound Quality (15).
The submission mapped a Beats headphone shopper journey using AIDA. It listed customer actions, thoughts, emotions, and key touchpoints from awareness to purchase, and described checkpoints like social media ads, product pages, reviews, checkout, and post-purchase updates.
Situation: a consumer survey on wireless speakers contained categorical and numeric responses. Task: quantify usage, satisfaction, and drivers. Action: cleaned data, converted categories to numeric, calculated means, medians, modes, correlations and segment counts. Result: a quantitative analysis…