David Patton

David Patton has a diverse and extensive work experience. David is currently working as a Lead Data Scientist at CareFirst BlueCross BlueShield, where they lead a team in performing exploratory data analysis, model development, and deployment. David also communicates insights to both business and technical leadership and is responsible for transitioning the organization to a data science/machine learning approach.

In addition to their current role, David has worked as a Co-organizer at Deep Learning Adventures Meetup, where they presented material, developed code and models, interviewed industry experts, and recruited members. David also worked as a Data Scientist at A3.AI, conducting data analysis, modeling, and research on COVID-19 data, as well as working on data privacy preservation and clinical embeddings.

Before that, David worked as a Data Science Consultant at Fusion Studios LLC, a Trader in a self-employed capacity, and as the Director of Government Practice at CC Pace, where they helped government agencies deliver efficient products using Agile methodologies.

David also has experience as a CTO at Friendlylook, a social network designed to help people make new connections. David built a highly scalable social network from scratch using open-source software and databases on the Amazon AWS Cloud platform.

Furthermore, David worked as an Independent Consultant at DCPatton, LLC, where they delivered web applications, listened to client needs, and provided accurate projections of effort required. David was also the CTO of LinkKite, LLC, where they led the development of the linkkite.com beta application using Ruby on Rails.

Lastly, David served as the Director of Technology at TrafficLand, where they oversaw a team in delivering technical solutions and research for the real-time, video-based electronic information services provided by the company. David ensured the technical systems were robust and scalable.

Overall, David Patton has a strong background in data science, leadership, Agile methodologies, and technology development.

David Patton completed their education in a chronological order. David obtained a Bachelor of Science (BS) degree in Physics from The University of Memphis between 1987 and 1991. David then pursued a Master of Science (MS) degree in Physics from the University of Alabama at Birmingham, studying from 1991 to 1993. Finally, they completed their educational journey by earning a Doctor of Philosophy (PhD) degree in Computational Physics from the University of Alabama at Birmingham, attending from 1993 to 1996.

In addition to their formal education, David Patton has also obtained various certifications to enhance their skills. David holds the following certifications:

1. AWS Certified Machine Learning - Specialty from Amazon Web Services (AWS), obtained in October 2022.

2. AWS Certified Cloud Practitioner from Amazon Web Services (AWS), obtained in December 2021.

3. AI For Medical Treatment from Coursera, obtained in July 2020.

4. AI for Medical Diagnosis from Coursera, obtained in July 2020.

5. AI for Medical Prognosis from Coursera, obtained in July 2020.

6. AI for Medicine Specialization from Coursera, obtained in July 2020.

7. Advanced Deployment Scenarios with TensorFlow from Coursera, obtained in July 2020.

8. TensorFlow Developer Certificate from TensorFlow Certificate Program, obtained in July 2020.

9. TensorFlow: Data and Deployment Specialization from Coursera, obtained in July 2020.

10. Data Pipelines with TensorFlow Data Services from Coursera, obtained in June 2020.

11. Device-based Models with TensorFlow Lite from Coursera, obtained in June 2020.

12. Browser-based Models with TensorFlow.js from Coursera, obtained in May 2020.

13. DeepLearning.AI TensorFlow Developer Specialization from Coursera, obtained in May 2020.

14. Sequences, Time Series and Prediction from Coursera, obtained in May 2020.

15. Convolutional Neural Networks in TensorFlow from Coursera, obtained in April 2020.

16. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning from Coursera, obtained in April 2020.

17. Natural Language Processing in TensorFlow from Coursera, obtained in April 2020.

18. Deep Learning Specialization from Coursera, obtained in December 2019.

19. Sequence Models from Coursera, obtained in December 2019.

20. Convolutional Neural Networks from Coursera, obtained in September 2019.

These certifications reflect their dedication to continuous learning and staying abreast of advancements in the field.