About

Professional Headshot of Will McGinnis

Hi, I’m Will McGinnis

I’m an entrepreneur and data science executive with over a decade of experience at the intersection of AI/ML, technology, and business strategy. Currently, I serve as the Executive Director and Head of Data Science for Aumni at JPMorgan Chase & Co., where I lead AI/ML in the VC and PE space.

Background

My educational background is in Mechanical Engineering, in which I received a B.S. and M.S. from Auburn University. My research work in undergrad and graduate school focused on multi-body dynamics and system wear, using large scale numeric simulations and optimization techniques to understand and improve wear performance in complex aerospace systems.

While in school, I worked a few different jobs: quantitative analyst at a commodities hedge fund TS Capital (long story), process engineer at a battery manufacturing plant, and a research engineer at the Naval Surface Warefarce Center’s Panama City Directorate.

After receiving my M.S., rather than continue with the Ph.D. as planned, I met Mario and joined Predikto as a co-founder. Predikto was a startup taking an AI/ML approach to the system wear and reliability problems I had been working on. We focused on distributed assets (rail, shipping, aerospace, etc.) and grew the company through 2 rounds of institutaional fundion, dozens of customers around the world, and a small scrappy team.

In 2018, Predikto was acquired by United Technologies (UTC), and I joined UTC’s Digital & Analytics group as a leader in their Applied Data function. In this role, I led analytics projects across the corporation, including a focus on digital transformation and advanced machine learning techniques for performance optimization in defense and industrial systems. Part of the way through we merged with Raytheon in one of the largest mergers in history, and I continued to lead Applied Data for the combined company.

In 2022 I joined Aumni after their Series B to start the data science function focused on data montetization, AI-powered data extraction, content marketing, and other interesting applications of AI/ML. This went well and in 2023 we were acquired by JPMorgan Chase & Co and and absorbed into their Strategy and Growth Office in corporate.

Professional Experience

JPMorgan Chase & Co.
Executive Director & Head of Data Science, Aumni | 2023 – Present

  • Led the Data Science team at Aumni in JP Morgan’s Strategy and Growth Office, focusing on AI, ML, and advanced analytics in the VC and PE space.
  • Developed large scale document processing, valuations, predictive modeling, and entity resolution using technologies like GenAI and semantic search.
  • Achieved significant impact through the implementation of tabular and time series ML models, resulting in improved research and indices.

Aumni
VP of Data Science, Aumni | 2022 – 2023

  • Led data science team at Aumni, utilizing legal documents to build leading VC dataset.
  • Developed enterprise BI, led product development, conducted research, and applied machine learning.
  • Acquired by JPMC in May 2023, showcasing successful leadership and data science expertise.

Raytheon Technologies / UTC
Senior Director, Applied Data | 2018 – 2022

  • Oversaw transformative analytics projects with a focus on digital innovation and strategic applications.
  • Directed multidisciplinary teams in leveraging advanced machine learning techniques for performance optimization in defense and industrial systems.
  • Managed large-scale, cross-functional projects that enhanced operational efficiencies and data-driven insights.

Predikto
Technical Co-Founder & Chief Scientist | 2013 – 2018

  • Pioneered the development of a predictive maintenance platform that set new standards in asset management for heavy industry.
  • Utilized state-of-the-art machine learning algorithms to drive performance improvements and risk mitigation.
  • Played an instrumental role in scaling technology operations, leading to a successful acquisition and integration into a larger corporate structure.

Skills & Expertise

  • Data Science & Analytics: Machine Learning, Statistical Modeling, Predictive Analytics, Generative AI, RAG, Semantic Search
  • Software Engineering: Full-Stack Development, Scalable Architecture, Cloud Computing, Distributed Systems
  • Leadership: Team Building, Strategic Planning, Digital Transformation
  • Industry Focus: Financial Services, Defense, Aerospace,Industrial Maintenance

Publications

  • Category Encoders: a scikit-learn-contrib package of transformers for encoding categorical data
    Journal of Open Source Software (January 2018)

  • Maintenance Triage: Identifying Sick and Injured Assets to Improve Population Health
    Uptime Magazine (February 2015)

  • Modeling and Simulation of Missile Launcher System Wear During Captive Carry
    Auburn University (August 2014)
    Masters thesis developing a multibody simulation based approach to simulating wear in complex rattling systems.

  • Missile Launch System Wear Study and Wear Modeling for Sandy Environments
    61st JANNAF Propulsion Meeting (May 2014)
    A multibody-simulation based approach to wear simulation for Hellfire missile launcher systems.

  • Simulation and Validation of a Low Power Regime Based Attitude Determination and Control System for CubeSats
    AMSE Early Career Technical Conference (November 2013)

  • CubeSat Attitude Determination and Control Study and Realization
    Cal Poly CubeSat Workshop (April 2013)

  • Parameter Estimation and Simulation Using Virtual Elevation Methods For Race Cycling
    Auburn University Journal of Undergraduate Scholarship (April 2013)

Open Source Contributions

I’ve contributed to the open source community, particularly within the Python data science ecosystem. Some notable projects include:

  • Category Encoders: A scikit-learn-contrib package of transformers for encoding categorical data.
  • Elote: A Python package for rating algorithms like Elo and Glicko.
  • Git Pandas: A Python package for using git with pandas DataFrames.

Let’s Connect

When I’m not leading transformative AI projects or shaping data‑driven strategies, you’ll likely find me cycling, skiing, or enjoying quality time with my wife and daughter.

I always welcome the opportunity to connect with like‑minded professionals who share a passion for data science and technology.