September 13, 2017
Once you’ve decided it’s time to go to a coding school, you’ll want to make sure the one you pick is worth it and provides value. We sat down with Paulo Arantes, an alumni to the Galvanize Data Science program who is now a Machine Learning Engineer at UnifyID in San Francisco.
He came to Galvanize with eight years of business strategy and entrepreneurship, helping entrepreneurs scale their business. He is passionate about AI, technology and futurism and in his role with UnifyID is working with deep and shallow learning…”so you never have to remember/type your password again.” He shares with us his memories of the Galvanize program as well as advice to current and future Data Scientists.
Tell us about your current company and role.
UnifyID is working on an implicit authentication platform, meaning that you can just be yourself and you will be automatically authenticated (or de-authenticated) automatically without any conscious action, like typing a password or using a fingerprint. We are at the intersection of deep learning and security and can learn what makes you unique by the way you behave, the way you move, and the sensors around you. My routine as an engineer here is a mix of research and fast paced experimentation. We are a startup and need to move fast, but we are also a startup that publishes papers to contribute to the academic community (we presented in all major machine learning conferences and had seven papers in the past three months accepted by peer review). Since we work with human motion, I get to play with lots of sensors, designing experiments, capturing data and dealing with the processing pipelines, but also get to write/test production code and train various neural networks and classifiers on our GPU clusters. Only this year we won RSA, SXSW Security, MIT AI Idol, and raised a $20 million series A to boost growth.
As you have interviewed, hired, or worked alongside new team members, what is the most important quality you look for (skills, trait, personality)?
I enjoy working with people coming from different backgrounds that have a mindset of teaching and learning constantly and can be flexible to adapt in this scenario of academic rigor and fast deliveries.
Thinking back a bit…what inspired you to join the Galvanize program?
I’ve always used data to make strategic decisions, but was limited by my team’s expertise and Excel macros. I wanted to be able to build and execute my ideas from a technical understanding and perspective. Once I decided data science was a way to merge my business experience with technical skills, I interviewed about 15 people that were Data Scientists and decided that Galvanize was the best and fastest option to break into this industry.
What was your favorite part of your immersive experience?
The variety of backgrounds from my colleagues was the best part. There were people from 19 to 60+ years old, coming fresh from undergrad until PhDs. And we all struggled together in different areas/parts of the program, being able to support each other’s growth constantly. We attended many events together and learned together during job searching – so it’s the community in general.
Was there anything you wish you’d focused on more during the program?
Complete honest, the program was great for what’s designed to do: give you an understanding of every technology and technique available and teaching you how to learn. The day to day goes by so fast that it was impossible for me to dedicate more time to anything else, meaning: I am completely satisfied with what I could learn.
Technologies change very fast (from a paper publication to code implementation in GitHub in 24 hours), so learning how to learn was the most valuable skill. The pair programming taught me how to learn other people’s coding/working style. Not that there was a lot of time, but I recommend people should spend their time right after graduation not directly job searching (if they can afford this luxury), but by joining hackathons and getting involved in more projects after the Capstone – it was the best way to keep learning.
What helped you the most during your job search?
A: The coaching sessions with Galvanize were amazing to deeply understand what transformation I wanted to have in myself given the new skill sets I acquired during the program. Career services were great to practice white-boarding and share take home stories (also having 6 months membership to use the space was awesome to attend events and see all my colleagues job searching together). Besides all the advice and tons of moral boost whenever I needed (and we all needed, rejection hurts, but it’s a numbers game since “data science” is such a broad field), keep learning after the program and putting my skills to practice with hackathons, competitions, and startups was the most effective way to start getting job offers.
What’s next for you?
I plan to stay at UnifyID for the long run and keep studying and learning more about machine learning in general. There’s so many sensors around us and making sense out of them to make life easier and safer is a very hard problem to tackle, but the impact can be huge, which keeps me motivated.
Final advice for a student currently in a Galvanize immersive program, about to start their technology job search?
It’s going to be hard. When I decided to join, I thought it would be as easy as “spend 3 months, get a high paying job right away.” But the transition is not automatically and it’s truly up to you to get a dream job. [Galvanize] will help you, a lot. But in the end what matters is you discovering what you want to do, the path you want to develop yourself into, and a lot of hard work. Galvanize is the best way to start this journey, but it’s only the beginning. You should never stop learning new exciting things, applying to jobs like crazy (personally, it took me 186 customized applications to find what I was looking for) and iterating over each outcome to keep getting better. And get real life experience by joining events, competitions, hackathons, working with startups in small projects, etc.
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