INTERESTS: Work, outdoors activities, and dating.
Tell us more about where you are from and what shaped you:
I’m originally from Pittsburgh. I went to Carnegie Mellon and got a degree in economics, which I got because it is the default major to do when you don’t know what you want to do. I moved out to Los Angeles a year after school for the first job and only job offer I received after college. I never thought of going to CA or Los Angeles, and it was crazy because I said I would go anywhere and I ended up going to LA, which is a freaking cool city. I came up to the Bay Area after 5 years in LA to attend 42.
What did you do before 42?
Following college, I worked as a data analyst at two different companies. I left my last job to start a social media company. My company was a platform for social media influencers to capture the value of their audience in a way that most social networks did not allow. We gave influencers a platform and pre-built features to engage and monetize their super fans. My work experiences are all related to data and I really like working with data, particularly in driving company strategy with your analyses. After 42 I decided to continue pursuing data because I enjoy the strategic element of companies, and I felt as an engineer I would have limited exposure to that.
Did you have any programming experience before 42?
Part of starting a social media company afforded me the opportunity to experiment with web development, but it wasn’t until 42 that I really began to grasp the technical foundations of programming.
What did you like best about your 42 experience?
I liked the pedagogy. I think a lot of people don’t appreciate the purpose of the pedagogy. It’s designed to teach the fundamental concepts that are present in all computing-related disciplines, and in doing so it empowers students to tackle any technical problem. The difficult part of the pedagogy, and one that I encourage students to actively evaluate, is that it does not teach job relevant technologies, at least for most jobs. I always advise people to follow the pedagogy through at least one entire branch before they shift their focus to higher level languages.
Is there anything that you do now at work that you don’t think would come as easily if you hadn’t attended 42?
I am still in a technical role, I need to use computers and navigate them and understand the tradeoff between doing things. I think specifically, 42 has helped me understand how to use APIs and how to understand how computers are networked together. It has helped me become really good at using the command line, and it has given me the vocabulary that allows me to communicate with very technical people.
As mentioned earlier 42 has given me the base skill set to tackle any technical problem. Because of that when I encounter issues or have to learn new technology I am equipped with the knowledge to handle those tasks. In Data Science not only do I script and work with databases, but I have to understand how the software whose performance I am evaluating functions, and 42 provided the knowledge base to do that.
How did you get your foot in the door where you work?
I had applied to my company 2 or 3 times, and then a friend I met at 42, his ex-girlfriend worked here, and she was able to get me on the phone with one of the hiring managers before I got the phone screen. It was through that process I was able to impress upon them that I was capable. It is difficult because when you are evaluating someone on a piece of paper, like through a resume, it isn’t enough information to know the person.
Describe what you do:
I am responsible for the collections department of a FinTech company. When you loan out money and people become delinquent, you need to collect on that, and I am in charge of those processes. For this, I have build purpose, I have built out extensive reporting using SQL and Python. I also do ad hoc analyses that support strategic decisions. The tools I user are Python, Jupyter Notebooks, command line, SQL, Statistics and Excel to name a few.
What does your typical workday look like?
I usually get in around 8:30 am, we have a standup meeting at 9:15 am where I give an update on how collections is doing. After that I get breakfast and coffee, check email and get my tasks ready for the day, so it is all administrative. In the afternoon I follow up on the things I need to do, whether an analysis or checking requirements with stakeholders. In the afternoon I get 2-3 solid hours to do data analysis. I usually leave work around 7 pm. Data science has long hours because whatever you do, you can always go deeper.
Would you recommend the 42 program and if so, why?
Yes, I would recommend it. The curriculum and community at 42 create an environment that allows motivated people to grow. Because of this, in a couple of years, you and your classmates will be scattered around the bay doing cool projects at a variety of companies. The caveat is that it is very hard to get a job after 42. I believe this is the case for most graduates of non-accredited schools. When I recommend 42 I make sure to emphasize this and encourage people to look at job postings early in their time so that when they are ready to look for a job they are already prepared for the specific skills they will need. That being said it’s also essential that you spend a good deal of time on the C curriculum, that is the knowledge that will set you apart in your career.
Do you have any advice for 42 students when it comes to securing an internship or job?
There is no secret weapon or silver bullet as they say. I would say my biggest tip is to understand and commit to a specific job (it’s ok to change jobs, but commit to one and figure out if that’s what you want). Say you are into data science you can do machine learning, data analysis, etc. In the field you are interested in you need to know where you can provide value so you can double down on that and make it a thing you do. You need to analyze job postings and it is through that process you can see what people are looking for. Job postings are a cheat sheet for what will be on the job test, the interview. Once you’ve looked at 50+ job postings you’ll start to get a sense of the terms companies use, the technologies they use, and what level of job the posting is for. So go through the job postings and hopefully go through some interviews, then repeat until you’re an expert on applying for that specific job. It is a negative process, you need to hustle.
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Photos provided by Zack Smith