Data Scientist & MLOps Engineer based in Lagos, Nigeria, with 3+ years of experience building end-to-end ML systems and analytics solutions across Retail, E-commerce, Finance, and Crypto markets.

I don't just build models — I ship production systems: secured REST APIs, automated retraining pipelines, CI/CD workflows, and cloud deployments that run themselves. My work spans the full stack from raw data ingestion to live interactive dashboards.

What sets my work apart:

• Production-grade pipelines with automated testing, drift detection, and audit trails
• Crypto-native financial engineering (not a copy-paste of equity assumptions)
• Systems designed for zero daily human intervention
• Clean, modular, documented code — built to be handed off

Production-grade cryptocurrency price forecasting pipeline built entirely in R

• Pipeline: Yahoo Finance → DuckDB → 15 technical features → ARIMA → Plumber API → Shiny dashboard
• Automation: GitHub Actions cron (02:00 UTC daily) — retrains, validates, detects model drift
• Security: X-API-Key auth, rate limiting, CORS, no secrets in code
• Testing: 35 automated tests (14 data integrity + 6 feature + 11 modeling + 1 integration)
• Performance: BTC-USD RMSE 0.0233 (~2.3% daily error) · ETH-USD RMSE 0.0358 (~3.6%)
• 🌐 Live Dashboard: https://e9yw5n-kayterthesly.shinyapps.io/crypto-price-pipeline/
• 🚀 Live API: https://crypto-price-pipeline-production.up.railway.app/health

Binary classification system predicting 30-day hospital readmission with Retrieval-Augmented Generation (RAG) clinical decision support

• Target: readmitted_30d — primary metric Recall ≥ 0.85, Precision ≥ 0.50
• Data: MIMIC-IV Demo OMOP seed data, synthesised to ~50,000 patients via synthpop
• RAG layer: Clinical notes via ellmer/Gemini API → Ollama/Llama 3 transition strategy
• Stack: R · tidymodels · DuckDB · ellmer · Gemini API · Llama 3
• Stage: Data scaffold and synthesis pipeline — active development

• Nigerian Retail Coupon Dashboard — Excel + MySQL + Power BI (end-to-end BI pipeline)
• Coupon Redemption Prediction — Python ML + Power BI (predictive analytics)
• Business Analytics Curriculum — 29-day R + Python course for Aptech Centre, Lagos (Nigerian fintech case studies)

• Advanced ML techniques with tidymodels and Scikit-learn
• Retrieval-Augmented Generation (RAG) for clinical NLP
• LLM integration in R via ellmer and Ollama
• Web3 and blockchain analytics
• Funded MSc programmes in Data Science (target: 2026–2027)

Continuous improvement — not perfection on day one, but better with every commit.

Every project I ship follows a disciplined, stage-by-stage process: verify the foundation before building the walls, write tests before deploying, automate what other people do manually. The crypto-price-pipeline went through 40 commits across 8 production stages — each one verified before the next began.

That is what separates a portfolio project from a production system.

Open to remote Data Scientist · MLOps Engineer · Analytics Engineer · ML Engineer roles
Kingsleya402@gmail.com