Skip to content
View Johnnysnipes90's full-sized avatar

Block or report Johnnysnipes90

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please donโ€™t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this userโ€™s behavior. Learn more about reporting abuse.

Report abuse
Johnnysnipes90/README.md

๐Ÿ‘‹ Hi, I'm John Olalemi

๐Ÿš€ Data Scientist | Machine Learning Engineer | AI Engineer
๐Ÿ“ Lagos, Nigeria
๐Ÿ“Š Business-driven analytics โ€ข ๐Ÿค– Applied machine learning โ€ข โš™๏ธ Production-ready data systems


๐Ÿ” About Me

I am a Data Scientist and Machine Learning Engineer with a strong background in Statistics and Computer Engineering, focused on building end-to-end, real-world data and ML solutions.

I work at the intersection of:

  • Business problem-solving
  • Statistical rigor
  • Machine learning engineering

My projects emphasize clean data pipelines, interpretable models, and production readiness, not just experimentation.
I am currently expanding into AI Engineering, working with LLMs, RAG systems, and model deployment.


๐Ÿง  Core Skills

๐Ÿ“Š Data Science & Analytics

  • Exploratory Data Analysis (EDA)
  • Statistical Modeling & Hypothesis Testing
  • Time Series Forecasting
  • A/B Testing & Experimentation
  • Business Intelligence (Power BI)

๐Ÿค– Machine Learning

  • Supervised & Unsupervised Learning
  • Feature Engineering
  • Model Evaluation & Optimization
  • Imbalanced Learning (Fraud & Churn)
  • NLP & Text Similarity

โš™๏ธ Engineering & MLOps

  • Python, SQL
  • Pandas, NumPy, Scikit-learn
  • ML Pipelines & Experiment Tracking
  • FastAPI (Model Serving)
  • Git & GitHub
  • Docker (Learning)

๐Ÿง  AI Engineering (In Progress)

  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • Vector Databases
  • LLM-based Applications

๐Ÿ“Œ Featured Projects

๐Ÿ“Š Retail Sales Intelligence & Forecasting System

  • End-to-end BI solution using Python, SQL, and Power BI
  • ETL pipelines transforming raw transactional data
  • Time-series forecasting for revenue planning
  • Executive-ready dashboards and insights

๐Ÿค– Fraud Detection Machine Learning System

  • Tackled extreme class imbalance
  • Optimized precisionโ€“recall trade-offs
  • Business-focused evaluation for financial risk reduction

๐Ÿ“ˆ Customer Churn Analytics & Segmentation

  • Cohort and behavioral analysis
  • Customer segmentation using clustering
  • Actionable retention strategy recommendations

โžก๏ธ Explore repositories below for full project details.


๐Ÿ› ๏ธ Tech Stack

Languages: Python, SQL
Libraries: Pandas, NumPy, Scikit-learn
BI Tools: Power BI
ML Tools: MLflow, DVC (learning)
Deployment: FastAPI, Docker (learning)
Version Control: Git & GitHub


๐Ÿ“ซ Letโ€™s Connect


โญ Open to Data Scientist, Machine Learning Engineer, and Applied AI roles
โญ Actively building production-grade projects

Pinned Loading

  1. Movie-revenue-prediction Movie-revenue-prediction Public

    End-to-end ML pipeline predicting high- vs low-revenue movie titles using engagement, ratings, and robust cross-validation.

    Jupyter Notebook 1

  2. retail-sales-bi-dashboard retail-sales-bi-dashboard Public

    End-to-end Business Intelligence solution built with Python, SQL, Power BI, and DAX. Features star-schema modeling, centralized KPI governance, YoY/YTD analytics, customer Pareto analysis, and execโ€ฆ

    Jupyter Notebook 1

  3. Automated-Stock-Market-Data-Pipeline Automated-Stock-Market-Data-Pipeline Public

    Automate daily extraction of stock prices, validate and transform the data, load into a PostgreSQL feature store, and expose a Streamlit dashboard that refreshes automatically. Orchestration by Airโ€ฆ

    Python 1

  4. fraud-detection-api fraud-detection-api Public

    A production-style fraud detection system that scores transaction fraud risk using XGBoost, evaluates performance with time-based and rolling validation, tunes thresholds for business tradeoffs, anโ€ฆ

    Jupyter Notebook 1

  5. ai-job-search-copilot ai-job-search-copilot Public

    AI-powered job search copilot built with FastAPI, Streamlit, RAG, and agent orchestration for resume-job fit analysis, cover letter generation, and multi-step AI workflows.

    Python 1

  6. ai-data-analyst-copilot ai-data-analyst-copilot Public

    AI-powered analytics copilot that converts natural-language questions into SQL, executes queries, generates business insights, and visualizes results using RAG, agent orchestration, and FastAPI + Sโ€ฆ

    Python 1