About

I'm Laura Grace Ellis, a cybersecurity AI executive and the author of the blog Little Miss Data.

I'm Vice President of Data and AI at Rapid7, where I lead a large engineering organization at the intersection of data infrastructure and AI-powered cybersecurity products. My work has spanned both sides of AI at scale: the internal data and AI systems that run the business, and the product engineering teams that bake AI capabilities directly into SaaS offerings for customers. I speak and write about AI and security regularly, across industry events, press, and analyst conversations.

Little Miss Data is where I share what I've learned about AI, data, and what it actually looks like to build and lead these systems at scale.

What I Write About

My blog has evolved alongside both AI and my career. Content spans:

Agentic AI and SOC Automation covers how AI is reshaping security operations, and what it takes to build reliable agentic systems in production.

AI Governance and Ethics covers practical approaches to responsible AI deployment, from policy-setting to building governance frameworks that actually hold up.

AI Leadership covers the organizational and strategic side of leading AI teams, scaling engineering orgs, and making bets in a fast-moving space.

Data Engineering and Architecture covers the foundational systems that make AI work at scale.

Accessible Data and AI Tutorials are hands-on guides for practitioners and those just getting started.

Areas of Expertise

Agentic AI Systems | AI Governance and Ethics | Cybersecurity AI | LLM and Generative AI | Enterprise AI Strategy | Data Engineering and Architecture | Engineering Leadership | Data Literacy | Stakeholder Engagement | Strategic Planning | Industry Communications

Career

Rapid7, Vice President of Data and AI (2023 to Present) Leading a large, multinational engineering organization responsible for both internal data and AI platforms and the AI and data capabilities embedded in Rapid7's SaaS cybersecurity products.

Rapid7, Vice President of Data Engineering and Platform Analytics (2022 to 2023) Built and led the cross-portfolio internal data platform, driving modernization of the core data stack and enabling business-critical analytics across the organization.

IBM Corporation, Technical Director and Analytics Architect, IBM Cloud (2016 to 2022) Developed and executed technical strategy for IBM Cloud's internal data platform, leading a 20+ person team across data infrastructure, analytics, and ML integration.

Earlier roles at IBM spanning databases, data systems, data science, master data management, program management, and partner programs (2005 to 2016).

Education

  • CARNEGIE MELLON UNIVERSITY in Pittsburgh PA,

    Chief Data Officer Executive Certificate

  • NORTHWESTERN UNIVERSITY in Evanston IL,

    Master of Science in Predictive Analytics

  • UNIVERSITY OF WESTERN ONTARIO in London, ON,

    Bachelor of Engineering Science, Software Engineering

Certifications

  • Certified PMP®

  • Open Group Data Science Profession, Certification Level 1 & 2

  • Certified DB2 DBA

Awards

Affiliations

  • Co-founder & Co-host, Data Mishaps Night

  • Member, WLDA Women Leaders Data Association

  • Mentor, WLDA Ventures

  • Content Council (2022, 2024), DataConnect Conference

  • Member – Austin Women in Data Groups (R Ladies Austin, R Austin User Group, Women in Data Science Austin, Women in Tech Austin)

  • Member (2022-2023), Amplitude Customer Advisory Board

  • Co-chair (2019-2022), IBM Internal Patent Review Board

  • Badge Approver (2019-2022),  Open Group Certified Data Scientist

  • Image Consultant (2019-2021), Dress for Success Austin

  • Member (2021-2022), IBM Academy of Technology

  • Member (2018), NASA Datanaut

Contact