Lead Machine Learning Engineer2013 - PRESENTStreamEdge Analytics, LLC.
Technologies: Scikit-learn, Keras, TensorFlow, AWS, GCP, Git, GitHub, Python, Pandas, Jupyter, NVIDIA GPU
- Responsible for the design and implementation of specific components of the Xfinity Voice Assistant Platform that is used by millions of customers every day. Lead engineer on Comcast Labs Applied AI research and engineering team that owns the full stack and operationalization of voice product offerings, as well as advanced analytics and the machine learning pipeline work. Used advanced machine learning and Cloud technologies to process the billions of natural language queries received every year, and to make a user’s input actionable. (http://dclabs.comcast.com).
- Supported the $1.2 billion contract with Centers for Medicare Services and worked as the lead machine learning engineer on the project. I focused on predictive modeling, machine learning, and data mining on a large healthcare dataset. SERCO-NA (https://www.serco-na.com).
- Developed predictive models to improve the effectiveness of child support collection activities and monitoring of the health and safety of children in foster care. I oversaw the project as the lead machine learning engineer. Information Builders (ibi.com).
- Developed multi-terabyte Automated Vehicle Location data sets consisting of the operational details of public transportation systems for major metropolitan transit systems as the lead big data analytics engineer. I applied advanced data mining, statistical inference, and machine learning techniques to identify unsafe operational practices in public transportation systems.
- Supported the special activities for the Chairman of the Joint Chiefs of Staff, and Office of Secretary of Defense, and Defense Manpower Data Center. I engineered and managed mission-critical manpower analytics and logistics systems.
- Collaborated as the teaching and technical assistant to the lead instructors for the Predictive Analytics for Healthcare workshop of the largest conference on Predictive Analytics.
Machine Learning Software Engineer2017 - 2018Greensmith Energy (Acquired by Wärtsilä)
Technologies: Python, Scikit-learn, Pandas, Numpy, Gurobi Optimizer
- Developed the machine learning and analytics software for the simulation and optimized operation of advanced renewable-energy storage systems. (ref: https://singularityhub.com/2019/07/21/machine-learning-vs-climate-change-ai-for-the-greener-good/).
- Designed and developed energy market trading optimization algorithms and applications.
- Designed and developed Greensmith Energy's first real-time energy market trading process that makes use of advanced optimization models. Ran the models through a 30-day operational test with Électricité de France, the world's largest producer of electricity. (https://en.wikipedia.org/wiki/Électricité_de_France).
- Designed and developed an energy analytics framework, including energy management optimization, machine learning-based forecasting, and simulation services.
- Proposed and led design, acquisition and, implementation of Greensmith Energy's largest software acquisition for embedded enterprise and reseller licenses of Gurobi Optimization and Mathematical Solver into Greensmith's Energy Management and Control System (GEMS), CD/CI pipeline, and GEMS Cloud and remote customer deployments.
Senior Software Engineer, Business Intelligence Specialist2005 - 2013Independent Consultant
Technologies: Java, Python, Cognos BI, Tableau
- Developed for various federal, DoD, intelligence communities, and Fortune 500 companies as an enterprise software engineer and business intelligence consultant.
- Provided expertise on a variety of data extraction methods that would facilitate the State of New York's compliance with Hearst's FOIA request. I was the expert technical witness for Hearst Publishing in Hearst vs. State of New York (https://casetext.com/case/hearst-v-state-of-ny).