Women in STEM

Building a career in technical analytics was challenging without role models or mentors early on. I’m grateful for the people who shaped my career, and now mentor other women.

Women often apply only for jobs where they meet every qualification, while men apply when they meet 60%. Confidence closes that gap, and anyone can help build this for women by:

Encouraging them to apply when they meet most of the qualifications.
Recommending them for projects, promotions, and speaking slots.
Hiring for skills, not titles. In underrepresented fields, women often do the work of a title they don’t hold. AMD hired me as a data engineer, a title I’d never held, but I had been building databases and reporting architecture for years.

Why diversity matters

Technology built by a homogeneous team underserves everyone else. The first airbags, engineered by an all-male team, caused fatalities among women and children.

Research shows an underserved group needs a critical mass to be represented. Women earned 37% of computer science degrees in the mid-1980s. A rapid decline followed, partly attributed to computer advertisements targeting boys.

People I follow

I look for women in technical and leadership roles. Beyond online inspiration, find women in your area to trade ideas in person.

Mindi Weik specializes in software and APIs, and every conversation with her fuels my curiosity. We met through Women&TECH Colorado.
Christina Ernst of She Builds Robots combines sewing, 3D sculpting, and robotics.
Tara Mohr wrote Playing Big, which a mentor recommended to me. Her list of weak words that undercut women’s voices, like “just” and “actually,” is built into this site’s prose lint.
Mel Robbins keeps me in touch with the human side of business. As an intensely analytical person, I need the reminder: life is more than an algorithmic game to master. Her Let Them Theory reminds me to relax and not take life too seriously.

Women who inspire me

Beyond these regular sources, the technical accomplishments of several women innovators shaped my career. I’ve listed them by their influence on me.

Grace Hopper seated at the UNIVAC I console in 1957, reading a printout with three colleagues

Photo: Smithsonian Institution, 1957, CC BY 2.0

Harvard Mark I, 1944; A-0 compiler, 1952

Grace Hopper

Hopper’s formal education began at Vassar and culminated in a master’s and Ph.D. in mathematics from Yale, completed in 1934. She then taught mathematics at Vassar until World War II.

After Pearl Harbor, Grace applied to the Navy and was rejected for being too old, underweight, and a critical resource as a math professor. Hopper persisted, received a waiver, and was assigned to the Mark I, the first electromechanical computer in the U.S. It calculated rocket trajectories and anti-aircraft range tables.

Grace saw tedious, error-prone machine code as a blocker to scaling computer programming. In 1952 she developed the A-0, one of the first compilers. She then pushed for programs written in English, a concept deemed impossible. She dedicated three years to getting the idea accepted. Her team’s FLOW-MATIC became the first programming language to use English commands, directly shaping COBOL.

Her ideas about compilers and human-readable code underpin modern languages like Python and C++. I see a direct translation from her work to today’s natural-language AI compilers.

Grace was proudest of the young people she had trained, and I hope to leave a similar legacy.

Portrait of Lisa Su in a blue jacket against a black background

Photo: CTA via PR Newswire

AMD CEO, 2014 to present

Dr. Lisa Su

At AMD, I see women treated as technical equals, and they regularly hold leadership roles. AMD’s slogan is “Together We Advance.” Watch Dr. Lisa Su speak at conferences around the world and notice she consistently gets leaders working together to advance technology.

Dr. Su joined AMD in 2012 and became CEO in 2014. She took AMD from the brink of bankruptcy, with its stock below $2 in 2015, to a $1 trillion market value in September 2026.

She has an intense curiosity about how things work and chose electrical engineering at MIT because it seemed like the most difficult major. As a Ph.D. candidate, she was one of the first researchers to explore silicon-on-insulator technology, a then-unproven method to make transistors more efficient. A thin insulating layer under each transistor blocks charge from spilling into the silicon below. Chips built this way switch faster on less power.

Dr. Su regularly encourages others to “run toward the hardest problems.”

Cassie Kozyrkov speaking on stage at Web Summit 2018, gesturing with both hands in front of a screen of code

Photo: Harry Murphy/Web Summit, CC BY 2.0

Google's first Chief Decision Scientist, 2018 to 2023

Cassie Kozyrkov

A well-known speaker in AI and analytics, Cassie Kozyrkov uses her theater training to craft engaging public speaking events. She began university at 15 and established the field of decision intelligence through her role as Google’s first Chief Decision Scientist. Kozyrkov personally trained over 20,000 Googlers in AI and data-driven decision-making and now leads her own company. She has an abundance of thought-provoking posts on Medium.

I particularly love her equation for public speaking:

Useful + Amusing = Amuseful

Portrait of Ada Lovelace in a white satin gown and tiara

Portrait: Margaret Sarah Carpenter, 1836. Public domain via Wikimedia Commons

Analytical Engine notes, 1843

Ada Lovelace

A century before Grace Hopper programmed the Mark I, Ada Lovelace wrote an algorithm in pen and ink. The machine it ran on existed only on paper. Her mother, Annabella Milbanke, insisted on an unusually rigorous education in mathematics. She wanted to steer Ada away from the temperament of her literature-loving father, the poet Lord Byron. Lovelace went on to study much of an undergraduate mathematics curriculum privately with mathematician Augustus De Morgan.

In 1843, at 27, she published an English translation of Luigi Menabrea’s paper on Charles Babbage’s Analytical Engine. The publication included seven extensive notes of her own. The last laid out an algorithm for computing Bernoulli numbers on Babbage’s machine, which was never built. While working on the algorithm, she caught a serious mistake in Babbage’s own calculations.

Ada saw that the machine could work with symbols, not only numbers. She wrote, “The Analytical Engine weaves algebraic patterns, just as the Jacquard loom weaves flowers and leaves.” Her idea was published a century before the first electronic computers and is the foundation of every computer we use today.

In the mid-1800s, women were not allowed to formally attend universities. Her mom saw her talents and was determined to advocate for her future. Similarly, my mom has been a force in my life who has always believed I could do anything I set my mind to.

Margaret Hamilton
Annie Easley
Katherine Johnson
ENIAC programmers

Margaret Hamilton: Photo: Draper Laboratory, 1969. Public domain via Wikimedia Commons
Annie Easley: Photo: NASA, 1981. Public domain via Wikimedia Commons
Katherine Johnson: Photo: NASA, 1966. Public domain via Wikimedia Commons
ENIAC programmers: Photo: U.S. Army, 1946. Public domain via Wikimedia Commons

Margaret HamiltonMIT Instrumentation Lab, 1965 to 1976
Margaret Hamilton led the Software Engineering Division at MIT’s Instrumentation Lab, which developed the Apollo guidance computer. Her team built its onboard flight software. That software saved the Apollo 11 landing when the guidance computer overloaded minutes before touchdown on the moon. She insisted on the term “software engineering” to give writing code the same respect as hardware engineering. The idea was considered humorous at the time.
Annie EasleyNASA Lewis, 1955 to 1989
Annie Easley spent 34 years at NASA’s Lewis Research Center, from 1955 to 1989. She started as a “human computer,” doing calculations by hand for engineers, and learned programming when machines took over the work. Her code supported the Centaur rocket stage, which later launched missions such as Cassini to Saturn. She also served as an Equal Employment Opportunity counselor, helping address discrimination complaints based on race, gender, and age.
Katherine JohnsonNASA Langley, 1953 to 1986
Katherine Johnson began working as a human computer in 1953. Eight years later, she calculated the trajectory for Alan Shepard’s Freedom 7, the first American spaceflight. A year later, John Glenn asked her to check the new IBM computer’s calculations for his orbit by hand before he would fly. He trusted her work more than the machine’s. She worked at NASA until 1986, and her story was later told in the book and film Hidden Figures.
The ENIAC programmersENIAC, 1945 to 1946
Kay McNulty, Betty Jennings, Betty Snyder, Marlyn Wescoff, Fran Bilas, and Ruth Lichterman programmed ENIAC, the first general-purpose electronic computer. They worked without manuals, relying only on wiring diagrams. The project was classified, and at first they weren’t allowed in the same room as the machine. The women programmed it by setting switches and routing cables by hand.

Their ballistics program was the centerpiece of ENIAC’s 1946 unveiling, but the newspaper photos of the event named only the men. At the time, programming was seen as clerical work; the credit went to the men who built the hardware. They were finally recognized in 1997, when all six were inducted into the Women in Technology Hall of Fame.