What I Learned at NYC Uncubed 2018

What I Learned at NYC Uncubed 2018

Every year, Uncubed hosts a 1-day conference (NYC Uncubed) featuring a fair to connect people with start-up and tech careers. I attended the event in Brooklyn with data science positions in mind and here’s what I learned.

  • Bring physical copies your resume.

    • Print out a few copies of your resume for the event because HR personnel like to mark it up with notes as they speak to you.
    • You can be as aggressive with this as you want. I saw a lot of people with fancy folders filled to the brim with resumes. I brought 5 copies and that was plenty. The amount you bring should be reflective of how interested you are in the hiring companies announced ahead of the event.
  • Lower your expectations.

    • Don’t expect every single recruiter to blow your mind with the work you’ll be doing. Uncubed talks about how this is ‘New York City’s Top Recruiting Event for Digital Talent’, but the reality is that most companies in attendance weren’t revolutionary. If handling health insurance data floats your boat, this might be the conference for you.
    • Not every company is there to offer technical roles. Only a handful of companies out of the total 44 in attendance had openings in data science.
    • Instead of speaking to you about open roles, some companies will simply tell you to refer to their job boards because they’re not sure what specific openings are available.
    • This event isn’t going to change your life if you’re looking for entry-level positions. People straight up want you to have 3-5 years experience for many of the technical roles.
  • Prepare to be judged.

    • Get ready for: “Have you considered attending a bootcamp?” followed by “Where did you even take these classes?” and “I don’t see how any of this experience is relevant.”
    • Telling recruiters that you’re self-taught can freak them out. Some people are super nice and understanding, while others can’t fathom the possibility that you might be changing careers.
  • You don’t need to stay the whole time.

    • The event has a content session from 10:00 AM-1:00 PM and the employer showcase from 1:00 PM-5:00 PM, followed by a casual networking session.
    • The content sessions are something that’s nice, but not essential. It’s mostly people talking about the work they do for their companies in various positions, including data science, human resources, and marketing.
    • Four hours is a bit excessive for the company showcase. If you’re looking for a role in a specific field, it’s best to give yourself 1 to 2 hours to speak to employers. I was finished visiting the companies with data analyst openings by 3 PM.

It was an educational experience to learn the expectations of recruiters and to attend the content sessions. Honestly, I don’t see myself attending NYC Uncubed again. Instead, I’ll focus on industry-specific talks and networking events as future professional growth opportunities.

Why I Started Reading More Often

This year, I began to read more books thanks to a social media hiatus between January and March. I logged out of Facebook, Instagram, Twitter, and Snapchat and deleted the apps on my phone. I knew I spent way too many hours scrolling mindlessly through photos and status updates.

My intention was to renegotiate my use of free time to focus solely on learning and self improvement. I decided to find books at the library on topics for data science, coding, and topics of general curiosity.

An assortment of books on a shelf.
A section of my personal library including books that I have not yet finished.

Self education through reading has helped me confront some of my general anxieties about topics I find challenging. In 2018, I have read books focusing on mindfulness, coding, personal finance, business management, and behavioral psychology. I still enjoy reading books in my comfort zone of science and conservation, but I think it’s helpful to understand other fields of interest.

Instead of basking in my blatant ignorance about retirement plans and investments, I’ve been trying to read more books about business and finance. Learning about topics I find totally foreign has forced me to realize it’s simple and rewarding to address ignorance head-on.

Additionally, a few of the books I have read this year are just for pure fun. Authors like Reshma Saujani (founder of Girls Who Code) and Tim Ferriss (lifestyle coach extraordinaire) inspire me endlessly so I chose to read books by each of them. I appreciate how books can provide a platform to connect readers with mentors from any field.

I hope to keep the momentum going and maintain my current reading habits for the rest of the year. In that spirit, I have designated a new page for my reading list and I include a few notes on each book.

 

5 Tips for Debugging Your Life

5 Tips for Debugging Your Life
A collection of beetles of various sizes, shapes, and colors sits in a glass container at a museum.
Beetle collection at Buffalo Museum of Science in Buffalo, New York, 2017

One of my first lessons as a new programmer was to learn how to debug code. Debugging means to review your code to find errors and correct them accordingly. Entire programs can be thrown off by one stray keystroke. This made me think about how minor, or major, habits and mindsets were holding me back from achieving my full potential. Here’s some advice for how I edited my personal life to learn code on my own terms.

1. Be patient with yourself and embrace failure.

Messing up code is inevitable, so don’t take it too personally when it happens. This took me a few weeks to learn because my entire life I’ve always thought failure was unacceptable. I recommend being overwhelmingly patient with yourself because every mistake presents an opportunity to learn a valuable lesson. When you get to the point where your code is clean and runs properly, the feeling of accomplishment will overshadow struggles along the way.

2. Learn to say ‘no’ more often to things that no longer serve you.

Get comfortable with saying ‘no’ because it can keep you from wasting time doing things you don’t wholeheartedly want to do. Take a moment to see exactly where your time is going if you’ve got too much on your plate and want more time to code. I started to learn how to code last year when I was unemployed and did not have a job lined up. I was dedicating at least 40 hours a week to learning, but some of my peers still saw this as a vacation. I began to say ‘no’ to certain activities in order to spend more time improving my programming skills and less time with people who made me feel awful. It may take some careful revision to eliminate excess drains of your time to create a more refined schedule that will ultimately benefit your mental state.

3. Don’t be afraid to ask for help online or attend local events.

Programming communities are abundant both online and in person, depending on your location. There are online resources like Stack Overflow for asking questions. I’ve also used the live chat assistance feature on Codecademy multiple times when I had a problems that forums could not answer. Don’t be afraid to turn to virtual support networks when you need help because someone will probably be able to help you.

For in-person events, Meetup is an awesome way to find interesting talks and events for local developers. I was nervous before attending a coding meetup in my area for the first time. Ultimately, I was grateful I worked up the courage to attend because I got to meet some wonderful mentors. I also use Women Who Code to keep an eye out for chapter events and conferences in major cities. Depending on your specific interests, there are a number of organizations that can help and encourage you as a programmer.

4. Create a work environment that encourages productivity.

Your work space can easily influence your level of productivity. Recognize your habits and common sources of distraction, then tailor your work area to these considerations. For me, this means having a clutter-free work desk, a comfortable chair, and a room free of outside noises. I also get easily distracted by my phone, so I try to keep it on silent and out of reach. Additionally, I think it’s helpful to have some sort of physical notebook or online system for random notes and ideas you think about while programming. This can keep ideas organized but separate from specific class or project notes. I use Google Keep to jot down quick ideas, but there are other similar alternatives like Evernote.

5. Remember that there are many potential routes to reach the same destination.

There are multiple ways to program. People can write code differently and still yield the same end result. Similarly, there is not one singular route to success and personal fulfillment. Take pride in your ability to creatively problem solve and celebrate and respect diverse ideas when collaborating with others. There are many ways to learn and grow in programming but you ultimately get to decide what methods work best for you.

A Fresh Start

You might be wondering how I got here. Last December, I decided to take a break from my career in order to transition to a new professional path I found more fulfilling. I was sucked into the world of seasonal field technician gigs and I wanted out. I worked in three seasonal positions before moving back home to Syracuse, New York. I panicked and took a job at a construction company in Syracuse, and then quit after realizing that it wasn’t at all where I wanted my life to go. And this is where data science comes in.

I started looking up positions that I wanted and graduate programs that I dreamed of getting into. A common thread was that experience in programming languages like Python and R was a desired qualification for many job postings. This was where I could start changing my life around from collecting data to performing data analysis using programming.

Data science is a field where people use existing data to make predictions, create visualizations, and derive information from analysis to create a narrative for the data. A career in data science seemed like the natural next step for me.

I started off using Udacity. This website offers a huge range of online courses that combine video lessons with assignments in various programs, such as R. The Udacity course that I took was Data Analysis with R. It’s a free course that gives a great introduction to using R.

Currently, I am also taking courses through Codecademy. I took two free courses,  Learn Python and Learn the Command Line, and am enrolled in the Introduction to Data Analysis Pro course that costs about $200. Codecademy course length can range anywhere from 10 hours to 10 weeks, depending on subject.

I started this journey about two months ago and hope to keep making progress everyday. Besides Python and R, I also plan on learning about SQL through Codecademy.

See my About Me page for more information.