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We’re spending Women’s History Month with women leaders who are making history every day in the tech community. Read more about Melissa Fabros: Software Engineer at Kiva.
Every March we recognize the women who have shaped history—and now, we’re taking a look forward. From driving software development in large companies to maintaining thriving open source communities, we’re spending Women’s History Month with women leaders who are making history every day in the tech community. Melissa Fabros is a Software Engineer at Kiva. She comes to programming from the world of nonprofits and higher education. Melissa’s interest in programming started in middle school where she was one of the first girls to join the computer club. However, she majored in English and American Literature in college. She loved the way literature “codes” the human brain to build worlds and emotions in the imagination. Even in academia, Melissa still maintained her coding interests by making small web page projects. After a friend told her that reading good code is like reading good writing, her curiosity for coding and software was renewed. Since that conversation, Melissa went from teaching at the University of California (Merced) to taking part-time coding classes, interning at Google Summer of Code, graduating from Hackbright Academy, and then completing an open source internship at GitHub.
Many miraculous accidents.
That’s a hard question because the on-ramp to tech looks different for people coming from non-STEM backgrounds. If we count the first time that I was paid by a “tech related” company, that would be teaching at Hackbright Academy, an engineering education program for people identifying as women. I had already taken part-time front-end and back-end courses with Hackbright. Then I was selected to be a teaching assistant for the full-stack course. After that, I started teaching the part-time introduction to programming course.
My first coding job that I got paid for was Google Summer of Code (GSOC). I learned how to apply to GSOC at a Women Who Code meeting that GSOC staff also attended.
What I know about leadership is informed by my experience as a teacher. I consider myself still feeling my way around the tech industry, but I’m happy to share what I know to make the process easier for others. I’m very inspired by the technical leadership at Kiva when it comes to how to grow and mentor talent. The commitment to seeing a path forward for the people behind you as well as achieving the goal in front of you is a vision I’d like to keep close.
I wouldn’t have a career in San Francisco without community and mentorship. I was lucky enough to have a home base in Berkeley even though I worked elsewhere. In Berkeley, there are a great number of people who are eager to share their passion and interests.
Women Who Code also gave an important open source workshop where you could meet with representatives of open source projects and learn how to contribute to their projects.
San Francisco’s meetup ecosystem helped me learn more about topics I was interested in exploring. I targeted meetups that were expressly interested in reaching out to women and under-represented groups. I’m also a fan of the Write/Speak/Code community. I’ve found that my community at Hackbright Academy is astoundingly talented and happy to share their time and wisdom too.
I had the opportunity to teach an introduction to machine learning course in Morocco. I volunteer with Delta Analytics, a volunteer organization committed to data for change. The group democratizes machine learning techniques and knowledge by working on data projects with social impact organizations and by teaching introduction to machine learning classes and workshops in countries with fewer resources than the San Francisco Bay area. We’ve now delivered our introduction to machine learning curriculum in Kenya and Morocco, and we’re currently interviewing partners for 2019.
Teaching the course was a work-related and personal project. I volunteer my off hours at Delta Analytics, but I also work for Kiva.org which works pretty extensively in Africa. The Delta curriculum uses Kiva’s data and I have an opportunity to demonstrate how Kiva’s core values are creating opportunity for others at all levels of the organization.
The program was supported by the U.S. Embassy in Rabat, and we were inspired by all the young Moroccans looking for opportunities to use machine learning as part of their problem-solving toolkit.
My biggest career risk was switching from university teaching to tech. I was teaching academic writing across the curriculum classes at the University of California. I had invested so much time, money, and emotional energy into the field. Coming to grips with the idea that I wasn’t leaving a field, but adding to fields that I want to explore was hard. I needed to nurture the hopeful 12-year-old me who helped found the middle school computer club, rather than double-down on a career that had shrinking opportunities.
I’m looking forward to exploring topics in ethics and AI. I’m a fast.ai alumna and developed my interests and expertise in machine learning with this community. So I’m a fan of the fast.ai mission from Rachel Thomas and Jeremy Howard: if you teach machine learning and AI techniques to people of diverse backgrounds and experiences, you can empower people with new tools to solve their problems.
Want to know more about Melissa Fabros? Follow them on GitHub.
Want to learn more about featured leaders for Women’s History Month? Read about:
Check back in soon—we’ll be adding new interviews weekly throughout March.