R
Ronald Whited
About
Detail
Santa Barbara, California, United States
Résumé
Jobs
verified_user
0% verified
Senior Data&ML Team LeadNikeNov 2022 - Current (3 years 8 months)• Architected and implemented a scalable ML platform combining Apache Kafka, Spark, and AWS SageMaker to support predictive modeling for patient outcomes across millions of health records. • Designed MLOps pipelines with Docker, Kubernetes, Terraform, and MLflow, ensuring reproducibility, automated retraining, and 99.9% uptime in production environments. • Led a cross-functional team of 7 engineers and data scientists, driving delivery of LLM-powered automation systems using LangChain and OpenAI APIs to optimize patient engagement and care coordination. • Developed synthetic data generation pipelines (GANs, VAEs) to enhance model robustness and compliance in sensitive health data environments. • Built real-time prediction APIs using FastAPI- Senior Machine Learning EngineerDatabricksJan 2020 - Oct 2022 (2 years 10 months)• Designed and deployed NLP models using Transformer architectures for clinical risk scoring and early disease detection. • Built ETL pipelines on AWS (S3, Lambda, EC2, Glue) to process terabytes of structured (EHR) and unstructured (clinical notes, imaging metadata) health data. • Established cloud-native training environments with automated hyperparameter tuning, distributed training, and reproducibility tracking using MLflow. • Automated model retraining pipelines triggered by new data ingestion, reducing model drift and improving accuracy over time. • Collaborated with data governance and compliance teams to ensure HIPAA-compliant ML workflows. • Delivered AI-powered diagnostic tools with real-time clinical decision support dashboards u
- Senior Machine Learning EngineerMedical SolutionsNov 2018 - Dec 2019 (1 year 2 months)• Developed and optimized data pipelines for time-series financial data, improving support for risk scoring and fraud detection models. • Guided business analysts in SQL and data visualization best practices, enhancing data accessibility and adoption across departments. • Implemented slowly changing dimensions (SCD Type 2 and Type 4) to improve historical accuracy of customer and transaction data. • Automated ETL scheduling and monitoring with Apache Airflow, reducing manual interventions. • Partnered with IT teams to align data warehouse strategy with enterprise reporting needs. • Conducted statistical validation and retraining of segmentation models for customer targeting. • Built ETL processes to integrate multiple internal systems into
Education
verified_user
0% verified
- Master's degree of Science (Computer Science)Stanford UniversityJan 2012 - Jan 2018 (6 years 1 month)