About Me

Abigail Spencer

Welcome! I currently work at the National Geospatial-Intelligence Agency (NGA) as the Data Lead for the overhead satellite component of a large computer vision program. I specialize in transforming complex datasets into actionable insights through cross-functional collaboration and innovative solutions. With extensive experience in data strategy, management, analysis, and science, I'm passionate about leveraging data to drive informed decision-making and leading technical discussions across various domains and applications.

I excel in breaking down complex problems and building solutions that have immediate actionable insights and recommendations. My day-to-day consists of leading multiple cross-functional technincal teams in the acquisition, pre-processing, curation, and labeling of petabytes of high-quality training data for model development. This includes managing complex data pipelines, setting data priortizations, developing data team strategies, and conducting in-depth data analysis to ensure the highest quality data in support of state-of-the-art deep learning model development for national security objectives through geospatial intelligence.

I served in the United States Navy for eight years, with three overseas deployments as an intelligence analyst. This invaluable experience instilled a strong work ethic, attention to detail, and the ability to thrive in high-pressure environments. It's also where I got my start in data, working with complex datasets to provide actionable intelligence to commanders in the field. This is where I honed my analytical skills and learned the importance of clear, succint, timely, and most importantly, accurate communication of complex information to diverse audiences.

Education is a passion of mine, whether for myself or teaching others. I'm finishing my second Bachelor of Science degree in data science (graduating December 2026) with focuses on machine learning, statistical analysis, and data visualization. My personal projects includes full-stack and data application development; in fact, this website was built from scratch using Next.js (React), Tailwind CSS, and a postgreSQL database. After graduation, I plan to pursue a Master's of Science in Data Analytics Engineering to further deepen my expertise in engineering and analysis.

What I'm Reading

Up Next

The Design of Web APIs, Second Edition by Arnaud Lauret
View on Amazon

The Design of Web APIs, Second Edition

Arnaud Lauret

Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions by Allen B. Downey
View on Barnes & Noble

Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions

Allen B. Downey

The Nuclear Age: An Epic Race for Arms, Power, and Survival by Serhii Plokhy
View on Barnes & Noble

The Nuclear Age: An Epic Race for Arms, Power, and Survival

Serhii Plokhy

The Signal and the Noise: Why So Many Predictions Fail--but Some Don't by Nate Silver
View on Barnes & Noble

The Signal and the Noise: Why So Many Predictions Fail--but Some Don't

Nate Silver

Real-World Machine Learning by Henrik Brink, Joseph Richards, Mark Fetherolf
View on Amazon

Real-World Machine Learning

Henrik Brink, Joseph Richards, Mark Fetherolf

Fundamentals of Data Engineering: Plan and Build Robust Data Systems by Joe Reis, Matt Housley
View on Amazon

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

Joe Reis, Matt Housley

The Missing README: A Guide for the New Software Engineer by Chris Riccomini, Dmitriy Ryaboy
View on Barnes & Noble

The Missing README: A Guide for the New Software Engineer

Chris Riccomini, Dmitriy Ryaboy

Prisoners of Geography: Ten Maps That Explain Everything About the World by Tim Marshall
View on Barnes & Noble

Prisoners of Geography: Ten Maps That Explain Everything About the World

Tim Marshall

Algorithms by Panos Louridas
View on Barnes & Noble

Algorithms

Panos Louridas

How Charts Lie: Getting Smarter about Visual Information by Alberto Cairo
View on Barnes & Noble

How Charts Lie: Getting Smarter about Visual Information

Alberto Cairo

The Art of Statistics: How to Learn from Data by David Spiegelhalter
View on Amazon

The Art of Statistics: How to Learn from Data

David Spiegelhalter

Practical Deep Learning, 2nd Edition by Ronald T. Kneusel
View on No Starch Press

Practical Deep Learning, 2nd Edition

Ronald T. Kneusel

Data Structures the Fun Way: An Amusing Adventure with Coffee-Filled Examples by Jeremy Kubica
View on No Starch Press

Data Structures the Fun Way: An Amusing Adventure with Coffee-Filled Examples

Jeremy Kubica

Chernobyl Roulette: War in the Nuclear Disaster Zone by Serhii Plokhy
View on Barnes & Noble

Chernobyl Roulette: War in the Nuclear Disaster Zone

Serhii Plokhy

Math for Deep Learning: What You Need to Know to Understand Neural Networks by Jeremy Kubica
View on No Starch Press

Math for Deep Learning: What You Need to Know to Understand Neural Networks

Jeremy Kubica

Dive Into Algorithms: A Pythonic Adventure for the Intrepid Beginner by Bradford Tuckfield
View on No Starch Press

Dive Into Algorithms: A Pythonic Adventure for the Intrepid Beginner

Bradford Tuckfield

Bayesian Statistics the Fun Way by Will Kurt
View on No Starch Press

Bayesian Statistics the Fun Way

Will Kurt

The Great Heist: China's Epic Campaign to Steal America's Secrets by David R. Shedd, Andrew Badger
View on Barnes & Noble

The Great Heist: China's Epic Campaign to Steal America's Secrets

David R. Shedd, Andrew Badger

Deeper Knowledge

Recently Read