lenny/

Hello and welcome.
I am Eugene Lenny, an aspiring ML dev.

Software Engineering Student · Aspiring Machine Learning & Systems Developer

“I build ML systems and the full-stack products that ship them.”

01 / aboutbackground & focus

I am a Software Engineering undergraduate at Murang'a Institute of Technology with a strong technical interest in machine learning, quantitative models, and developer tooling.

Rather than theoretical prototypes alone, I focus on building functional systems: quantitative strategies backtested on historical currency feeds, encrypted desktop cloud tools, and financial terminal interfaces.

> Looking for introductory / junior ML engineering roles, software development apprenticeships, and summer internships.

02 / skillsgrouped by role
ML / AI
  • •Python
  • •PyTorch
  • •Scikit-learn
  • •NumPy / Pandas
  • •OpenCV
  • •HuggingFace
Data & Systems
  • •SQL (PostgreSQL / SQLite)
  • •DuckDB / Parquet
  • •FastAPI
  • •Docker
  • •Linux / Bash
  • •Git & GitHub Actions
Full-Stack
  • •TypeScript
  • •React / Next.js
  • •Tailwind CSS
  • •Rust (Tauri)
  • •Capacitor (Mobile)
  • •WebSockets
03 / work

Completed Projects & Repositories

click row to expand problem & implementation

term::projects
matches: 6/6
>$env:var(--lang)=
>Asia-POE (YENRange)ml
2025–now

Systematic range-breakout quantitative strategy in MQL5 for USD/JPY with an 8,200+ parameter optimization sweep and Python XML pipeline.

Problem →Manual, discretionary execution of USD/JPY range-breakouts introduces human timing variance, emotional execution errors, and backtest overfitting.
Result →8,200+ parameter sweep analyzed via custom MT5 XML pipeline; top candidate achieved Sharpe 7.64, profit factor 1.24, and 26.8% max drawdown.
Lang:
PythonMQL5
Stack:MQL5 · MetaTrader 5 · Python · NumPy · Pandas · XML Pipeline
[ github → ][ read case study → ]
>FinanceTrackerfull-stack
2025–now
>Call Screener (CallScreen)ml
2025–now
>Telegram-Drivefull-stack
2024–2025
>BB-Terminalboth
2024–2025
>Chat Application (Alpine)full-stack
2024–2025
contentlayer::active6 entries indexed
04 / stats

Language Focus & Real-time Stats

real-time API synchronization · zero placeholder data

language_focus::distribution6 completed projects
Python67% of projects
TypeScript33% of projects
MQL517% of projects
Shell17% of projects
Kotlin17% of projects
JavaScript17% of projects
Node.js17% of projects
Java17% of projects
SQL17% of projects
Rust17% of projects
leetcode::live_apirealtime_sync
handle@lennx-gif →
problems_solved0
difficulty_splitEasy 0 · Med 0 · Hard 0
statusActive Undergrad Learner
kaggle::communityml_exploration
handle@zyga1one →
focus_areasTabular, Time-Series & NLP
current_trackKaggle Learn & Feature Pipelines
toolkitPyTorch, Scikit-learn, Pandas
05 / contact

Open to introductory roles & internships.

If you have an entry-level software or machine learning opportunity, or want to review my code, feel free to reach out.

email: lennylumwaji@gmail.comgithub: @Lennx-giflinkedin: eugene-lumwajiresume: [cv.pdf] →all channels →