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rychrr/README.md

πŸ‘¨β€πŸ’» Ejike Ozonkwo Richard

Senior Data Engineer & Scientist | Building data platforms, ML systems, and AI agents that make it to production.

πŸ“ Lagos, Nigeria Β· 🌍 Open to remote contracts (EU / UK / Canada/ Global) πŸ“« erozonkwo@gmail.com Β· LinkedIn Β· GitHub


πŸš€ About Me

I've spent 10+ years building the systems that quietly power fintech, banking, Energy, FMCG and telecoms such as fraud detection engines, credit scoring models, next best action/recommendations engines, chatbots, AI Agents and pipelines that process billions of transactions. I work across the full data lifecycle: from raw ingestion and cleaning, to production ML, to the dashboards executives actually use.

Lately I've gone deep into LLMs and agentic AI β€” building workflows where models don't just answer questions, they get things done.

I care about reliable, well-tested, well-documented data. I don't over-engineer, I ship, and I write code thinking about whoever inherits it.


πŸ› οΈ Tech Stack

Data Engineering Apache Spark / PySpark Β· Kafka Β· Hadoop / HDFS Β· dbt Β· Airflow Β· Snowflake Β· BigQuery Β· ELK Stack Β· SQL / NoSQL Β· ETL/ELT Design

Cloud & Infra GCP Β· AWS Β· Azure Β· k8s. Databricks Β· Docker Β· Kubernetes Β· CI/CD (GitHub Actions) Β· Git Β· REST APIs

Machine Learning Python Β· PyTorch Β· TensorFlow Β· scikit-learn Β· XGBoost Β· SHAP / XAI Β· Clustering (DBSCAN, K-Means) Β· NLP

AI / GenAI LLMs Β· Autonomous AI Agents Β· RAG Β· Prompt Engineering Β· Recommender Systems ,Langchain,n8n. etc.

MLOps MLflow Β· Model Monitoring & Drift Detection Β· Feature Stores Β· Reproducible Pipelines

Analytics & Viz Power BI Β· Looker Β· Tableau


πŸ—οΈ What I've Built

Data & AI Platforms

  • ⚑ Real-time fraud detection platform β€” PySpark β†’ Kafka β†’ Airflow pipeline processing 50M+ transactions/day at sub-second latency
  • πŸ€– AI-as-a-Service platform β€” containerised model-serving layer exposing risk scoring, churn, and merchant analytics APIs to fintech partners
  • πŸ“Š ELK-based log analytics platform β€” near real-time network fault detection across 30M+ subscribers
  • πŸ” Automated settlement pipeline β€” replaced a 58-day manual process with a 2-hour automated run at 99% lower error rate
  • 🎯 Customer analytics suite β€” sentiment analytics, churn, propensity, RFM, and CLV models driving 29% churn reduction and 57% loan sales growth
  • 🏭 Group-wide industrial analytics platform β€” unified data models spanning cement, fertilizer, energy, and petrochemicals on a centralized warehouse
  • πŸ“± Digital analytics engine β€” AI-driven loan scoring, churn prevention, recommendations, and CLV management β†’ 22% growth in digital product acquisition

Automation & Efficiency

  • πŸ” Automated incentive settlement pipeline (Python + SQL) β€” replaced a 28-day manual process with a 2-hour automated run, 99% error reduction
  • πŸš€ MLOps standardization β€” accelerated model-to-production cycle by 70% via standardized pipelines, feature stores, and CI/CD enforcement
  • πŸ” XAI/governance framework (SHAP-based) β€” cut model review & regulatory approval timelines by 70%, sustained 99.9% model uptime via drift detection and automated retraining

Customer & Risk Analytics

  • 🎯 Customer analytics suite β€” churn, propensity, RFM, telemarketing optimization β†’ 18% churn reduction, 37% loan sales growth, 26% uplift in campaign response, conversion improved 21% β†’ 59%
  • 🧩 Customer segmentation (K-Means, DBSCAN) β€” powered 13 new tailored business propositions across sales, marketing, and CX
  • πŸ•΅οΈ Facial-matching fraud detection (DBSCAN on KYC embeddings) β€” eliminated duplicate SIM registrations, hardened identity verification at scale
  • πŸ’³ Loan pre-scoring model validation β€” built XGBoost challenger models achieving +8pp KS improvement; applied SHAP-based XAI for regulatory/credit-committee confidence
  • ⚠️ Quantitative risk modeling β€” VaR, Monte Carlo simulation, stress testing supporting ICAAP and Basel II/III capital submissions

πŸ“ˆ Impact at a Glance

Metric Result
Model deployment speed 70% faster
Pipeline error reduction 99%
Production model uptime 99.9%
ETL turnaround 28 days β†’ 2 hours
Conversion uplift 31% β†’ 59%

πŸ’‘ What I'm Working On

  • Building agentic AI workflows that automate real business tasks
  • Scaling dbt-based ELT architectures
  • Exploring how LLMs can augment traditional analytics , not replace it

πŸ† Recognition

πŸŽ–οΈ Queen's Young Leaders Award (2015) Β· Associate Fellow, Royal Commonwealth Society (2016) Β· YALI West Africa (2017) Β· CEO Recognition Award (2024)


πŸ’¬ Got a hard data problem and not enough hands? Let's talk.

πŸ“« Contact Me

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