Dec 2024 – Present · 1 yr 4 mos · Tulsa, Oklahoma, United States

• Data Collection & Preprocessing: Collected and cleaned large-scale datasets from multiple sources, improving data completeness by 25% through robust handling of missing values, outliers, and inconsistent formats using imputation, filtering, and statistical modeling techniques.
• 1) Model Development & Training: Built and trained machine learning models using supervised, unsupervised, and reinforcement learning methods for classification, prediction, and clustering. Optimized hyperparameters via grid search and Bayesian optimization, increasing F1-score by 18% and reducing error rate by 22%.
• 2) Model Evaluation & Validation: Evaluated models using accuracy, precision, recall, and AUC-ROC to ensure alignment with business goals. Achieved a 15–20% performance improvement over baseline models by selecting the best-performing models based on validation results.
• 3) Model Deployment & Integration: Deployed ML/AI models to production environments using AWS and Google Cloud. Monitored for performance drift and applied updates, enhancing model reliability and reducing downtime by 20%.
• 4) A/B Testing & Statistical Analysis: Designed and implemented A/B tests to evaluate marketing campaigns and customer segmentation strategies. Data-driven optimizations led to a 12% increase in campaign ROI.
• 5) Software Development & Engineering: Wrote clean, maintainable Python code and followed software engineering best practices. Worked with ML frameworks including TensorFlow, PyTorch, and Scikit-learn across the ML lifecycle.
• 6) Predictive Modeling & Feature Engineering: Developed predictive models (e.g., linear regression, decision trees, XGBoost, random forest) to support business forecasting. Conducted feature selection and model tuning, achieving up to 92% accuracy and a 30% improvement in forecasting precision.

Aug 2024 – Dec 2024 · 4 mos · Tulsa, Oklahoma, United States

• Conducted advanced data analysis to identify quality trends and root causes of failures, enabling process improvements and ensuring product compliance.
• Created dashboards and reports using Excel and Power BI to monitor key quality metrics and provide actionable insights for cross-functional teams.
• Utilized predictive analytics to streamline processes and support continuous improvement initiatives in manufacturing operations.