• Hello!
    I'm Michelle

  • I am a Technologist

About Me

Who Am I?

I’m passionate about solving big impactful problems with technology, particularly with Data and AI.
I have my MBA in Finance (from Kellogg) which I leveraged working as a financial quant. Then I transitioned to software engineering where I worked as a tech exec at Oracle and an entrepreneur. I'm now a tech executive and data scientist who is also a lead inventor on multiple patent filings. Previously, I founded a fintech startup that uses data science to help people invest in line with their beliefs and values. I'm a speaker on topics including AI, tech, innovation, and diversity.

Currently I'm a CTO at JPMorgan Chase in the data technology part of the consumer bank (Chase).





Feel free to get in touch if you would like to collaborate
or share San Francisco dining tips!

Contact Me
Giving Back


Advisory Board Member, MBAi Program

McCormick School of Engineering / Kellogg School, Northwestern 2021 – Present

Judge and Mentor, Code for Good

JPMC 2021 – Present

Coding Teacher, Under-represented groups

Railsbridge 2017-2018

Cups of coffee
Million Users Impacted
Countries Tech in Production
Languages Tech in Production
Some Recent External Events


I'm a speaker on topics including AI, tech, innovation, and diversity.

Data Science and Innovation: Overcoming Complexity to Drive Competitive Advantage at Chief Data and Analytics Officers – SF


Guest Lecturer: MBAi program Kellogg-McCormick Schools, Northwestern


Scaling Trustworthy AI to Create Tangible Business Value Chief Data and Analytics Officers – NYC


Agile and AI CDAO Apex - Online


Overcoming Challenges when implementing ML and NLP Technology Boardroom, Waters Tech


Increase Success of Automated Tech with Tactful Planning and Execution of AI DATAx – Online


AI in Banking Ai4 – Online


The State of AI in Banking Ai4 – Online


Opening Keynote: “AI Innovation Everywhere” ImpactAI – Silicon Valley



Northwestern University
Evanston, Illinois

Evanston, Illinois
Varsity Crew Team

Nine month intensive online program

One year intensive online program


Work Experience

JPMorgan Chase, CTO - Central AI/ML, Marketplace, Vocabulary, and External Data

(Former) Head of AI Innovation
2019-Present Silicon Valley, CA

CTO for Central AI/ML, Marketplace, Vocabulary and External Data, Consumer Bank (Oct 2021 - present)

  • Responsible end to end for all aspects of technology, strategy, and people management
  • Attract, hire, lead, and coach a new team from scratch including capabilities for design, project, agile, engineering, data, and managers
  • Manage multiple teams in multi-layer geographically distributed Data Technology org
  • Research, design and deliver v1 of Data Marketplace on AWS EKS (containerized cloud deployment)
  • Set tech strategy; design end-to-end data technology; build the pipelines, microservices and applications
  • Founded and run firmwide AI/ML Sharing Club for collaboration
  • AI Spokesperson for the firm, with more than a dozen speaking events to date.
Head of AI Innovation, Digital (Sept 2019 - Oct 2021)
  • Player/coach leading teams to ideate, build, train and productionize AI/ML technology at JPMC scale for Consumer, Business Banking, and Wealth Management customers with 90 products and 1.5 BN monthly logins
  • Create innovation pipeline funnel of 30 researched and vetted ideas
  • Use scientific process promoting 9 initiatives to flight, 12 models deployed, and 1 full AI system, including a stealth highly visible project to the CEO
  • I built 100+ ML models including NLP, deep learning (SNN, CNN, LSTM), with accuracy up to 98%, and a new API and web application MVP
  • Manage engineering team including all code reviews and sprints
  • Filed 5 AI/ML patents as Lead inventor (NLP, Deep Learning, GraphML)
  • Selected to demo our project at company-wide Innovation Week.

Data Simply, CEO / Co-Founder / Chief Data Scientist
2016-2019 Palo Alto, CA

  • Co-built SaaS data platform generating investing signals from text in company SEC disclosures, using data science and AI
  • Managed all data science, software engineering and product deliverables
  • Delivered 100MM+ automated insights for financial sentiment and sustainable investing (ESG) with streaming real time data
  • Deployed production data pipelines at scale with 99% automation
  • General Manager for the company; raised funding; partnered with industry leader for full integration into their platform.

Insight Data Science, AI Engineering Fellow
2018 San Francisco, CA

  • Selective program to build applied AI systems with group collaboration
  • Built cryptocurrency funds flow predictor achieving 98% precision
  • Created pipeline using blockchain, custom datasets, and machine learning
  • Applied Deep Learning to new $200BN Crypto asset class.

Ariba and Various Startups, Director, Product
2004-2015 Silicon Valley, CA

  • Software product management leader at three acquired companies
  • Defined and rolled out company-wide product roadmap for public company
  • Drove successful Asia launch of world's largest B2B marketplace
  • Led 12 PM teams from product conception through launch and lifecycle, with multiple user segments and delivery methods.

Oracle Corp, Group Manager, Financial Applications Engineering
1997-2004 Silicon Valley, CA

  • Managed Financial web application software engineering and PM teams of 40+ designing, building, and maintaining global SaaS enterprise software suite
  • Innovative approaches raised flagship iExpenses to market leader
  • Introduced agile for 12X faster to market for $XX MM revenue stream
  • Led customer adoption program to 100% referenceability.

My Portfolio

Some of My Projects, Volunteering, and Open Source Contributions

Reading the Minds of Central Bankers: Predicting Fed Funds Rate Changes Using NLP

Used machine learning (NLP) to predict rate changes purely from Central Bank meeting transcripts. Significantly beat the industry benchmark.

Presentation Code

How AI Can Reduce Your Customer Churn

Customer churn is the loss of customers. It's a key success metric for many businesses. It's also important because from an economic perspective, it costs much less to keep customers than to get new ones.


Ethereum Flow Predictor: Gazing into the Crypto Ball

Used Deep Learning to Predict Cryptocurrency Flows using Blockchain Data.


Code and Run the Business at Data Simply

Data science meets sustainable investing

Blog Post

Open Source: FinTech Sandbox

Community-contributed security master and ingest scripts for a variety of financial data providers

Learn More