Skincare Compatibility Checker
shippedML app that predicts whether a Sephora product is safe to add to your skincare routine. Gradient Boosting + VADER sentiment on 1M+ reviews across 2,400 products.
Pythonscikit-learnStreamlitVADERpandas
// system online
Aishah Abdul-Hakeem — Analytics Engineer
> Analytics Engineer
Turning messy data into pretty pipelines.
// 01 — about.md
About Me
I build systems that turn messy data into decisions. Currently completing my MS in Data Analytics & Visualization at Morgan State, with a Cornell University CS foundation and real production experience across pipelines, dashboards, and automation. I'm not looking for just any analytics role, I'm building toward engineering leadership at the intersection of data, systems, and scale.
loc: Baltimore, MDmail: aishah.a1809@gmail.com
// 02 — stack.json
Skills & Stack
Languages
Visualization
Data & Pipelines
Automation
Cloud
ML & AI
// 03 — career.log
Positions Held
Analytics Engineer Intern
June 2025 – June 2026@ Cornell University, AHDC-QMPS · Hybrid, Ithaca, NY
- ▸Automated dairy health data workflows using Python (pandas, NumPy) and Streamlit, cutting processing time from 1 day to under 2 minutes.
- ▸Designed and deployed end-to-end data pipelines to clean, standardize, and aggregate raw field data across farms.
- ▸Built interactive dashboards visualizing hygiene metrics for client and internal use.
- ▸Vibe coded a data entry app for data collection using lovable
- ▸Architected a scalable webhook pipeline using n8n and Meta WhatsApp Cloud API for real-time message processing at scale.
- ▸Designed a bilingual WhatsApp-based training platform using Airtable, Supabase, Cloudinary, and Lovable.
AI Challenge Participant — AI Architect & Technical Lead
March 2025 – April 2025@ MoVi Hackathon · Remote
- ▸Implemented a quantitative forecasting model for U.S. grid replacement integrating asset retirements, demand projections, and investment timelines.
- ▸Awarded AI Architect and Technical Leadership Excellence out of 40+ participants.
- ▸Led cross-functional team using Claude.ai and Perplexity; delivered visualizations via Plotly.ai and Lovable.
// 04 — portfolio/
My Portfolio
Farm Learning — Bilingual Training Platform
shippedWhatsApp-based training system for dairy farm milkers. Flip cards with EN/ES audio, Airtable backend, automated certificate delivery, deployed for real farm workers.
n8nAirtableWhatsApp APIJavaScriptSupabase
Deep Learning with Small Data
shippedReplicated key experiments from Brigato & Iocchi (2020) on CNN performance under data scarcity. Found augmentation hurts at N=10 on Fashion-MNIST — an interesting exception the paper noted but didn't emphasize.
PyTorchPythonCIFAR-10Google Colab