Currently an Extern @Beats By Dre
Third-year undergrad sharpening analytics skills through coursework and a Beats by Dre data analytics externship focused on consumer insights.
Projects include a Beats by Dre externship that extracted qualitative and quantitative insights from consumer conversations, plus coursework and practice work to build analytics tools and techniques.
Beats By Dre · ✅ Verified by Extern · ⏱️ In progress
A Beats by Dre externship in data analytics focused on extracting qualitative and quantitative insights from consumer conversations.
Built a full-stack analytics platform predicting procrastination risk across 32,000+ students and 10M+ interaction records, achieving 89% accuracy and AUC-ROC of 0.94. Designed administrator dashboards and AI-powered intervention workflows enabling data-driven student support.
Third-year undergrad sharpening analytics skills through coursework and a Beats by Dre data analytics externship focused on consumer insights.
I am a third-year software engineering student studying for a bachelor’s degree, focused on transitioning into data analytics. I have limited work experience and am completing a Beats by Dre externship in data analytics, where I analyzed consumer conversations to extract qualitative and quantitative insights. My main goal is to build specific technical and professional skills for an entry-level analytics role.
Externships
Beats by Dre Data Analytics: Qualitative & Quantitative Insights Externship
Beats By Dre
Experience
Data Analytics Extern — Extern
Beats by Dre · May 2026 – Present
Outreach & Data Lead
CCI Rwanda · May 2025 – February 2026
Project & Operations Management Intern
LadX · June 2026 – Aug 2026
Section Leader
Stanford Code in Place · Apr 2025 – Jun 2025
Rapporteur — Certa Foundation Africa AI Stakeholder Event
Certa Foundation · Oct 2024
Education
African Leadership University
BSc Software Engineering · Class of 2026
ALX Africa
ALX Data Analytics Programme
Skills
✅ Verified by Extern · ⏱️ In progress
A Beats by Dre externship in data analytics focused on extracting qualitative and quantitative insights from consumer conversations.
The work collected and analyzed consumer feedback about wireless headphones and produced structured artifacts from raw reviews. The deliverables included a ranked Pain-Point Chart with frequencies and exemplar quotes and an AIDA-based customer journey table documenting actions, thoughts, feelings, and touchpoints from awareness through post-purchase.
I produced a ranked Pain-Point Chart for wireless headphones listing comfort, connectivity, battery, sound, and ANC with reported frequencies and supporting quotes, and I created an AIDA-based customer journey table capturing actions, thoughts, feelings, and service touchpoints.
I collected user reviews, coded recurring complaints, and distilled the top pain points for wireless headphones. I reported frequencies and example quotes, producing a ranked list (comfort, connectivity, battery, sound, ANC) with supporting excerpts.
I mapped a headphone buyer journey using the AIDA framework. I listed customer actions, thoughts, feelings and touchpoints at each stage, and produced a table that captured awareness through post-purchase actions and service touchpoints.
Built a full-stack analytics platform predicting procrastination risk across 32,000+ students and 10M+ interaction records, achieving 89% accuracy and AUC-ROC of 0.94. Designed administrator dashboards and AI-powered intervention workflows enabling data-driven student support.
Analysed a multivariate time-series dataset of 43,000+ hourly records, combining air quality and meteorological variables to forecast PM2.5 levels. Engineered temporal and weather-based features, achieving an RMSE of 28.55 and improving on baseline performance.