Software Engineer, Data Experience Designer
Candida Haynes is an avid contributor to the local and global technology community, proud liberal arts graduate (Amherst College), and self-taught software developer who found her way to programming through an interest in social media tools and relentless curiosity about their underlying technology. She is passionate about civic engagement, voting rights, and helping people use technology to amplify their potential. Progressive experience – over ten years as an educator, program manager, and operations manager – informs her contributions as process manager, collaborator, and builder. She traversed a path of independent learning, attending lectures and study groups led by PyLadies, NYC Python, AppNexus, MongoDB, Legal Hackers, Data Driven, the Free Software Foundation, Women Who Code, and Noisebridge.
She sharpened her technology “chops” more formally as an open source trainee during Mozilla’s Ascend Project in 2014, where she gave her first lightning talk. At PyData NYC in 2015 she launched My Little Data in a Big Data World with a poster incorporating simple third-party computing and visualization tools. She presented at PyData SF and PyBay in 2016 and was invited to mentor student-activists at a hackathon sponsored by the inaugural Education Anew: Shifting Justice conference in Memphis, Tennessee that same year. Her team designed an app to connect students with resources and fellow activists in their local communities.
Currently residing in a conscious co-op community in Oakland, Candida continues to facilitate learning, building, and sharing at the intersections of data and technology. You will find her supporting the renaissance of historically underrepresented entrepreneurs at DevLabs, assisting emerging data scientists and engineers at UC Berkeley Extension, working with artificial intelligence and deep learning enthusiasts at Accel.ai, and singing around the Bay Area with underground artists.
In January 2018 Candida will expand her linear algebra study group to include more lifelong learners who want to study math in the East Bay.
If you are interested in data science you might have questions about personal data. What is it? Where is it? Where should you put it in order to preserve or explore it? What can it tell you? What do you even want to know about your digital self? How can this extended knowledge of self […]