Alex Buntrock

Led design and deployment of predictive analytics models using Python, TensorFlow, and scikit-learn, improving client decision-making accuracy by 28%. Directed a team of ML engineers to integrate AI-driven recommendation systems into client platforms, increasing operational efficiency by 35% and enabling real-time inference with sub-second latency. Architected cloud-based ML workflows on AWS and Azure; implemented CI/CD pipelines for model versioning and retraining; monitored performance with MLflow and Prometheus. Built deep learning models for image recognition with Keras and performed feature engineering to accelerate training by 30%, while mentoring junior engineers.

Implemented AI solutions for client analytics platforms and built NLP models for automated email and document classification, reducing manual processing by 45%. Designed and maintained cloud-based ML pipelines using AWS SageMaker and Azure ML; conducted hyperparameter tuning and model evaluation with cross-validation and AUC-ROC, improving accuracy by 18%. Collaborated with data engineers to create ETL pipelines for structured and unstructured data; automated reporting dashboards with Power BI; developed computer vision solutions for image classification and ensured AI governance and security in deployments. Provided technical guidance on ML best practices to client teams.

Built and deployed predictive models to enhance business intelligence and forecasting. Developed NLP pipelines for sentiment analysis and automated feedback evaluation. Executed data preprocessing, feature engineering, and model validation workflows for structured and unstructured datasets. Optimized models with scikit-learn and XGBoost, achieving about 15% performance improvement. Designed dashboards with Tableau, developed recommendation engines, maintained data pipelines, and mentored junior analysts. Conducted exploratory data analysis to identify patterns and anomalies.