Overview
Work History
Education
Timeline
Machine Learning Skills
MLOps
Programming Languages
Publications
Hi, I’m

Jason Scott

Silver Spring,MD
Jason Scott

Overview

10
years of professional experience

Work History

Optoro

Senior Manager, Data Science
04.2023 - Current

Job overview

  • Developing self-service chat bot to field common questions from clients based on external knowledge base.
  • Automated cloud-based training and deploy pipelines, freeing team labor for new initiatives.

Optoro

Staff Data Scientist
09.2022 - 04.2023

Job overview

  • Created classification models for predicting customer behavior, nearly doubling associated product revenue.
  • Achieved promotion to team management within one year, reflecting exceptional performance and leadership.

Johns Hopkins Applied Physics Laboratory

Machine Learning Engineer
10.2016 - 08.2022

Job overview

  • Developed hybrid AI-enabled tracking and data fusion perception systems.
  • Presented at 2019 Fall Track and Motion GEOINT Workshop
  • Led team that developed deep classification models on video, speech, and text to automate medical record transcription, leading to a sponsor funded multi-year program.
  • Built accurate deep time series forecasting models for COVID-19 metrics, surpassing previous benchmark by 30% mean average error.
  • Unlocked ability to leverage datasets with disjoint labels when training deep semantic segmentation classification networks.
  • Bumblebee Award for Championing Revolutionary Capabilities

M&T Bank

Quantitative Risk Analyst
05.2014 - 10.2016

Job overview

  • Forecasted losses over a $4B+ loan portfolio to give managers risk assessments necessary to optimize profit.

Education

North Carolina State University
Raleigh, NC

Ph.D. from Applied Mathematics
03.2015

Timeline

Senior Manager, Data Science

Optoro
04.2023 - Current

Staff Data Scientist

Optoro
09.2022 - 04.2023

Machine Learning Engineer

Johns Hopkins Applied Physics Laboratory
10.2016 - 08.2022

Quantitative Risk Analyst

M&T Bank
05.2014 - 10.2016

North Carolina State University

Ph.D. from Applied Mathematics

Machine Learning Skills

  • Foundation models and transfer learning
  • Information extraction and NLP
  • Deep learning, transformers, and UQ on deep models
  • Image classification, object detection and tracking
  • Reinforcement learning
  • Classification, regression, survival analysis, forecasting, clustering

MLOps

  • GCP (Vertex AI Pipelines, Kubeflow, Cloud Build/Run, BigQuery)
  • Airflow, Docker, Git, dbt
  • API development and CI/CD

Programming Languages

  • Python, MATLAB, C/C++
  • PyTorch, Hugging Face, SpaCy
  • SQL (Snowflake, BigQuery, MySQL)
  • Strong object-oriented design

Publications

1. S.L. Campbell and J.R. Scott, 2016. Auxiliary Signal Design for Failure Detection with Initial Prior Information. In Proc. IEEE Southeastcon 2016.

2. J.R. Scott and S.L. Campbell, 2014. Auxiliary Signal Design for Failure Detection in High Index Differential Algebraic Equations. In Proc. IEEE Conference on Decision and Control, Los Angeles, CA.

3. J.R. Scott and S.L. Campbell, 2014. Auxiliary Signal Design for Failure Detection in Differential Algebraic Equations. AIMS Journal on Numerical Algebra, Control, and Optimization 4.2, pp. 151-179.

4. S.L. Campbell and J.R. Scott, 2014. Asynchronous Auxiliary Signal Design for Failure Detection. In Proc. IEEE Conference on Systems, Man, and Cybernetics, San Diego, CA.

5. J.R. Scott and S.L. Campbell, 2013. Observer Based Fault Detection and Identification in Differential Algebraic Equations. In Proc. ASME Dynamic Systems and Control Conference, Palo Alto, CA.

6. J.R. Scott and S.L. Campbell, 2013. Observer Based Fault Detection in Differential Algebraic Equations. In Proc. SIAM Conference on Control and its Applications, San Diego, CA.

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