Olanite Richard

Richard Olamide Olanite

Machine Learning Engineer

I design and deploy end-to-end ML solutions across healthcare, finance, and operations transforming complex data into actionable intelligence.

PythonTensorFlowPyTorchScikit-Learn
About Me

Engineering Intelligence

I am a Machine Learning Engineer with a strong foundation in mechanical engineering and a proven track record of building and deploying data-driven solutions across business, healthcare, and operational domains. My work focuses on developing scalable machine learning systems that transform complex data into actionable intelligence. I have designed and implemented high-performing models including fraud detection systems, medical risk predictors, forecasting models, and computer vision classifiers using modern frameworks such as TensorFlow and PyTorch.

0.94
ROC AUC
Fraud Detection
98%
Accuracy
Medical Risk
E2E
Pipelines
Production Ready

ML Expertise

Deep learning & classical ML

Data Engineering

Pipelines & feature engineering

MLOps

Docker, Kubernetes, CI/CD

Performance

98% accuracy, 0.94 AUC

Core Technologies
TensorFlowPyTorchScikit-learnDockerKubernetesPythonSQLAWS
3+

Years Experience

10+

Projects Completed

20+

Satisfied Clients

Featured Projects

NYC Uber Fare Prediction
Machine Learning
R² = 0.81, RMSE = 0.236

NYC Uber Fare Prediction

Built and deployed an XGBoost Regression model to predict NYC Uber fares with high accuracy.

PythonXGBoostPandasScikit-learn
  • Engineered key features including Haversine distance, time-based indicators, and one-hot encoded weekdays
  • Cleaned and transformed large-scale ride data with optimized preprocessing pipelines
Synthetic Fraud Analysis
Machine Learning
Improved recall via SMOTE

Synthetic Fraud Analysis

Built and evaluated a Decision Tree Classifier for fraud detection with class imbalance handling.

PythonScikit-learnImbalanced-learnPandas
  • Applied SMOTE to handle severe class imbalance in fraud datasets
  • Identified critical fraud indicators: risk score and 7-day failed transaction count
Sentiment Analysis & Text Classification
NLP
99.6% accuracy, perfect F1-scores

Sentiment Analysis & Text Classification

Multi-class sentiment analysis pipeline with extensive model benchmarking and optimization.

PythonNLTKScikit-learnLazyPredict
  • Built pipeline using TF-IDF vectorization, SMOTE resampling, and Gaussian Naïve Bayes
  • Benchmarked 20+ models with LazyPredict and optimized via GridSearchCV
Cat vs Dog Image Classifier
Computer Vision
≈98% accuracy

Cat vs Dog Image Classifier

Transfer learning image classifier using InceptionV3 for binary classification.

PythonTensorFlowKerasInceptionV3Transfer Learning
  • Fine-tuned InceptionV3 with custom layers for binary classification
  • Built end-to-end workflow: preprocessing, training, evaluation, real-time prediction

Experience & Credentials

Machine Learning Engineer

Digital Fortress InstituteLagos, Nigeria
February 2025 – Present

Developed and deployed ML solutions across business, engineering, healthcare, and operations, automating workflows and improving forecasting accuracy.

Built fraud detection model (ROC AUC = 0.94)
Heart disease predictor (98% accuracy)
Deployed scalable ML solutions with Docker and Kubernetes
Created visualizations with Seaborn and Matplotlib
Leveraged SQL for ETL pipelines

Contract Manager

Baleo Product CompanyLagos, Nigeria
Mar 2018 – Jan 2023

Managed end-to-end contract execution in a high-paced printing press, introducing ML solutions to boost efficiency and client satisfaction.

Machine-failure prediction (64% accuracy)
Contract delivery forecast models
Churn prediction system (86% accuracy, 68% precision) with LightGBM
Improved maintenance planning and deadline accuracy

Let's Work Together

Have a project in mind or want to discuss? I'm always open to meaningful conversations and exciting opportunities.

Connect

Available for work

Open to full-time & freelance

Or email me directly at richardolaniteolamide@gmail.com