Michael McKenna, Developer in Boston, MA, United States
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Michael McKenna

Verified Expert  in Engineering

Generative Pre-trained Transformers (GPT) Developer

Location
Boston, MA, United States
Toptal Member Since
July 16, 2019

Michael is a data scientist and machine learning engineer. Most recently, he led CVS’s COVID-19 vaccine demand forecasting, liaising closely with the White House and the CDC as part of Operation Warp Speed. He spends his spare time working on AI ethics problems and is an advocate and mentor for queer AI developers. An experienced leader, Michael has overseen teams of data scientists on health, workforce, and industrial projects.

Availability

Part-time

Preferred Environment

Amazon Web Services (AWS), Git, Python, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Spark, PySpark, Computer Vision, Machine Learning, PyTorch

The most amazing...

...project I've coded is a demand diagnosis models to understand reasons for COVID-19 vaccine hesitancy across the USA. It saved hundreds of lives.

Work Experience

Senior Data Scientist

2019 - 2021
CVS Health
  • Served as lead data scientist on various machine learning development, experimentation, and workforce innovation projects providing the incremental annual value of XX million USD.
  • Responded to consistent urgent requests from the White House, CDC, and Operation Warp Speed leadership on capacity planning, second-dose adherence, and daily vaccine utilization.
  • Implemented a fully customizable suite of COVID-19 vaccine demand forecasting and demand diagnosis models. These models anticipated vaccine demand drops and highlighted potential areas for intervention.
  • Collaborated with lead designers to identify and address the impact of social determinants of health on low immunization rates, drawing on SHAP values and ethnographic data to design interventions.
  • Acted as a key contributor to CVS's enterprise-wide algorithmic bias policy which set out steps for monitoring and mitigating bias along protected class lines within AI systems.
Technologies: Artificial Intelligence (AI)

Data Scientist

2018 - 2019
Widget Brain
  • Led retail projects including demographic-based demand forecasting for a large supermarket, roster optimization for a large Australian cosmetics chain, and theatre attendance forecasting for a large Australian cinema company.
  • Delivered predictive maintenance models for a large shipping OEM, allowing a 66% reduction in sensors.
  • Implemented deep learning extensions (such as LSTMs) to the existing demand forecasting product.
  • Built production flows using NodeRed and deployed models using AWS serverless code tools.
Technologies: OR-Tools, Jupyter, PyTorch, Python

Research Officer

2016 - 2018
Australian National University
  • Built NLP machine learning models to predict the likely severity of identity theft case reports. Research officer on Australia's first large-scale study on identity theft.
Technologies: Jupyter Notebook, PyTorch

Generalized Demand Forecasting Model

Together with a team of data scientists, implemented and used a data forecasting suite including over 20 different models

Supermarket Demand Driver Model

Lead developer of a machine learning model using census demographic data to predict the success of supermarket promotions, expansions, and luxury items in a given area.

Operation Warp Speed Demand Forecasting

• Implemented a fully customizable suite of COVID-19 vaccine demand forecasting and demand diagnosis models. These models anticipated vaccine demand drops and highlighted potential areas for intervention.
• Responded to consistent urgent requests from the White House, CDC, and Operation Warp Speed leadership on capacity planning, second-dose adherence, and daily vaccine utilization.
• Collaborated with lead designers to identify and address the impact of social determinants of health on low immunization rates, drawing on SHAP values and ethnographic data to design interventions.

Languages

Python 3, SQL, Python

Frameworks

StrongLoop, Spark

Libraries/APIs

PyTorch, Pandas, PySpark, TensorFlow, Facebook API, Keras, Scikit-learn

Paradigms

Data Science, Agile Software Development

Platforms

Jupyter Notebook, Amazon Web Services (AWS), Azure

Other

Convolutional Neural Networks, Machine Learning, Artificial Intelligence (AI), Computer Vision, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Neural Networks, Deep Neural Networks, LSTM Networks, OR-Tools, GeoPandas

Tools

Git, Jupyter

Storage

MySQL

2016 - 2018

Graduate Diploma in Computing

Australian National University - Canberra, Australia

2013 - 2016

Bachelor's Degree in Law

Australian National Unviersity - Canberra, Australia