Professional Summary
AI/ML Data Scientist | Production ML Systems Expert | Business Impact Driver
Proven AI/ML leader with 4+ years transforming complex data into $1M+ business value through scalable machine learning solutions. Expert in end-to-end model development, from research to production deployment, with deep experience in experimentation design and stakeholder communication. Specialized in applied AI systems that drive measurable business outcomes across travel, e-commerce, and enterprise sectors.
Technical Skills
Core Competencies
- Production ML Systems: End-to-end model development, deployment, and monitoring
- Advanced Analytics: Predictive modeling, customer segmentation, time-series forecasting
- Experimentation & Optimization: A/B testing, statistical analysis, conversion optimization
- Business Intelligence: Stakeholder communication, ROI modeling, data-driven strategy
Technical Stack
- ML/AI Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost, LangChain
- Cloud & Deployment: AWS (SageMaker, EC2, S3), Databricks, Docker, MLflow
- Data Engineering: Python, PySpark, SQL, ETL pipelines
- Emerging AI: RAG systems, LLM integration, vector databases
Professional Experience
Expedia Group – Machine Learning Scientist (2023 – Present)
- Led cross-functional ML initiatives with Engineering, Product, and Business teams, ensuring seamless model integration into production systems serving 1.5M+ monthly users
- Architected scalable ML infrastructure supporting real-time inference for personalization engines, achieving 99.9% uptime and <100ms response times
- Established MLOps best practices including automated model monitoring, drift detection, and retraining pipelines, reducing model maintenance overhead by 30%.
- Mentored junior data scientists and collaborated with ML Engineers on production deployment strategies, accelerating team capability development
Expedia Group – ML Scientist Intern (2022)
- Predicted repeat search likelihood to improve engagement.
- Developed models feeding into recommendation systems.
- Validated model outcomes with statistical testing.
Divercity Inc. – ML Engineer Intern (2021)
- Built CNN-based ethnicity prediction models (90%+ accuracy).
- Applied feature engineering and optimization.
University of Louisiana – Graduate Research Assistant (2017 – 2022)
- Researched ML applications in engineering and CO₂ segmentation modeling.
- Optimized experimental design for predictive outcomes.
Education
- Ph.D., Systems Engineering – University of Louisiana at Lafayette, 2022
- M.S., Informatics – University of Louisiana at Lafayette, 2022
- M.S., Petroleum Engineering – Heriot Watt University, UK, 2016
- B.S., Civil Engineering – Obafemi Awolowo University, Nigeria, 2008
Key Achievements
- Generated $1.14M annual profit increase through AI-driven conversion optimization
- Reduced customer segmentation analysis time by 2000% (6 hours → 18 minutes)
- Achieved 92% accuracy in demographic prediction models for personalization
- Published 4 peer-reviewed papers on applied machine learning in engineering
- Established experimentation frameworks adopted across multiple teams