Michael McKenna, Developer in Melbourne, Victoria, Australia
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Michael McKenna

Verified Expert  in Engineering

Natural Language Processing (NLP) Developer

Melbourne, Victoria, Australia

Toptal member since July 16, 2019

Bio

Michael is a data scientist and machine learning engineer with a diverse background spanning retail, healthcare, and government sectors, working in both startup and large enterprise environments. He has an eclectic set of technical specialties, including causal inference for retail experimentation, instruction tuning for generative AI models, and auditing for algorithmic fairness.

Portfolio

Self Employed
Artificial Intelligence (AI), Azure, Generative Artificial Intelligence (GenAI)...
CVS Health
Artificial Intelligence (AI), Causal Inference
Widget Brain
OR-Tools, Jupyter, PyTorch, Python

Experience

Availability

Part-time

Preferred Environment

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

The most amazing...

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

Work Experience

CTO

2022 - 2024
Self Employed
  • Developed and implemented a comprehensive AI/ML ethics risk management process, resulting in agency-wide adoption and integration into legal and external agency procedures, reducing risks associated with advanced data-driven initiatives.
  • Spearheaded the review of 40+ data-driven and non-data-driven projects across the agency, leveraging data analysis and ethical frameworks to provide actionable recommendations that were highly valued by senior executives and the Ethics Committee.
  • Created an innovative generative AI application to assist government agencies in identifying potential risks, rewards, and resilience factors, demonstrating practical application of cutting-edge AI technology in the public sector.
  • Established a reputation as the agency's go-to expert on emergent AI/ML technologies, including generative AI, providing critical contributions to the agency's interim AI strategy, particularly in areas of cloud computing and experimentation.
  • Collaborated with subject matter experts to develop data-driven, contextually relevant case studies for training senior executives and staff, resulting in approximately 90% positive feedback and improved understanding of data ethics across the org.
Technologies: Artificial Intelligence (AI), Azure, Generative Artificial Intelligence (GenAI), Auditing

Senior Data Scientist

2019 - 2021
CVS Health
  • Served as a lead data scientist on various machine learning development, experimentation, and workforce innovation projects, providing an 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, causal inference, 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), Causal Inference

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.
2016 - 2018

Graduate Diploma in Computing

Australian National University - Canberra, Australia

2013 - 2016

Bachelor's Degree in Law

Australian National Unviersity - Canberra, Australia

JUNE 2024 - PRESENT

Certified Information Security Manager

ISACA

APRIL 2024 - PRESENT

Certified Information Systems Auditor

ISACA

OCTOBER 2022 - PRESENT

Certified Information Privacy Technologist

IAPP

JULY 2019 - PRESENT

Admitted Legal Practitioner

Supreme Court of Victoria

Libraries/APIs

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

Tools

Git, Jupyter

Languages

Python 3, SQL, Python

Frameworks

StrongLoop, Spark

Platforms

Jupyter Notebook, Amazon Web Services (AWS), Azure

Paradigms

Agile Software Development

Storage

MySQL

Other

Convolutional Neural Networks (CNNs), Machine Learning, Artificial Intelligence (AI), Computer Vision, Natural Language Processing (NLP), Data Science, Generative Pre-trained Transformers (GPT), Causal Inference, Neural Networks, Deep Neural Networks (DNNs), LSTM Networks, OR-Tools, GeoPandas, Generative Artificial Intelligence (GenAI), Auditing, Legal, Privacy, Cybersecurity Operations

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