How I Became a Data Analyst by Optimizing the Right Place And time
Among my family and friends, I’m known as the go-to guy for findings deals on practically anything. Cars, phones, furniture you name it. I have probably purchased any product at an amazing price. The thing is though, I don’t have any special contacts or secret formula to find out when and where to get a great deal. I’m just prepared to strike the opportunity when it arises, learn where the deals usually occur, and most importantly; I’m patient. I guess those three points are the secret formula.
I hear it all the time from family and friends,
“How are they so lucky to get a dream job like that?”
“How did they land such an amazing partner?”
“Are you kidding me? They get to work remotely whenever they want?”
Here’s the thing though, I bet they weren’t just lucky, they were probably working towards beating the odds the entire time. You can’t eliminate the luck factor completely, but you can tilt it in your favor. I’ll walk you through how I tilted the odds in my favor when looking to change careers from an auditor to a data analyst.
(The first part of this article is more about how I was in the wrong place, ill-prepared for a data analytics role, and how I discovered to go down the data analytics path. If you want to skip these details then jump straight to the header: Heading towards the right place).
In the wrong place
Right after I graduated high-school I went to a university in U.A.E. to become an architectural engineer. I knew I enjoyed working with math and was passionate about working with something tangible, so this seemed right up my alley. The problem I ran into early on was the fact that all of my calculus and physics professors taught the class primarily in Arabic. Conversationally, the most I could muster would be, “wahid dejaj sandweech, minfadlik” which translates to “one chicken sandwich, please”. Understanding how to find derivatives would be a stretch.
For the goal of becoming an architectural engineer, this was absolutely the wrong place for my personal goals. I knew I had to make a move, but my father’s stipulation was that if he was going to pay for school, it had to be in Asia (higher education is way cheaper there). I made a deal with him. I asked him to buy me a ticket to the states, and a little money for a car, and I’d take care of the rest. Surprisingly he agreed (thanks dad!), and I was on my way, but tragedy struck soon after I arrived.
When I got to Texas I bought myself a ride, 1999 Nissan Altima, with over 83,000 miles on it! It was a complete piece of garbage, but it was my first piece of garbage car, and I loved it. (It was so bad I had to use a screwdriver to change gears).
Moving on from that, I tried to enroll in UT Austin’s architectural program, but they would not transfer any of the credits, I would have to start from scratch. I was already 2 years into my prior program, and didn’t want to graduate at 24. I was pretty bummed out at this point as I had my heart set on becoming an architect. This was around the time “How I Met Your Mother” was airing, so I thought being an architect like Ted Mosby would be beyond the bees knees.
After talking to family and friends, I shuffled my feet around and decided to become a financial auditor. Yeah I know, what was I thinking? At the time it made perfect sense. I knew two things about me, which still ring true today; I like playing with numbers, and I loved continuously learning. Financial auditor at the time seemed to fit the bill, and a lot of my credits would transfer over. I graduated with a dual degree in finance and accounting at the ripe old age of 23, got a job as an auditor at GameStop, became an audit consultant at an audit firm, worked for one of the biggest pharmaceutical distributors, and it turned it was the most monotonous career ever.
Reviewing financials and processes was not the kind of playing with numbers that I wanted, and after a few cycles, I didn’t feel like I was learning anything new. I became a soul-less cubicle wraith, drifting in and out of work every day. Again, I was in the wrong place.
After working as an auditor for 4 years, I knew something had to change. I was in the wrong place all over again, and if I didn’t make a change now, I was afraid it may be too late.
During one of my last few jobs I was also responsible for reporting the overall team progress of our audits. I found that small part of my job the most enjoyable. I got to work on its aesthetics, organized the information and designed the charts to make it as readable as possible. It was fun. Then I started playing with the numbers to see if I could predict how much earlier (or later) we’d complete a given audit. Then it hit me, I’m actually having fun at work. What if I could do this all the time?
I started reading up on different analyst roles, talked to people at work, and soon discovered that my company had our own data science team. My wonderful director knew some of the people within the data science team, and set-up an interview with them. I did my best to demonstrate my enthusiasm, and what I had self-taught, but it wasn’t enough. I wasn’t prepared enough for the role.
Heading towards the right place
After my first set back on not getting a role on the data science team, I asked for another meeting with the hiring manager to understand what skills I lacked and where I needed to shore up. The advice he gave me was solid:
Learn SQL and Python or R
Work at a smaller company, preferably a tech start-up
Having a good command of SQL was necessary just to simply query any database. It was as basic of a skill to an analyst as Excel is to an accountant. Learning a language like Python or R would be crucial in providing more analytical insights, and pave a pathway towards a data science career.
Looking for work at a smaller company was also genius. Start-ups are starved for resources, so even if you have some technical skill, you can bet you’ll be borrowed to help out other teams. This was literally positioning myself to be in the right place.
I was off to the races. I knew where I wanted to land, and I had a rough road map on how to get there. First I started taking a SQL and Python course from Udacity. It was a great resource that helped me learn the basics of both SQL and Python, along with lessons on using specific Python libraries for analytics, such as Numpy and Pandas. If you’d like to see the exact course that I took, check out the link below (the link below is an affiliate link and I may be compensated if you purchase a course):
Udacity
Click here to see the online course I used to learn SQL and Python!
At the same time I started to look for jobs at smaller companies. Even if I wasn’t 100% prepared, I wanted to try to land interviews, tweak my resume, and learn as much inside information as I could. I had to optimize every angle possible.
Many companies where I lived (Columbus, OH) were large established companies with a lot of hiring resources, so I had to widen my search. I started looking for jobs in New York and San Francisco. A great resource was www.builtin.com. BuiltIn is focused on providing jobs from smaller tech start-ups in areas like New York, San Francisco, Denver, Austin, etc. It was a great resource to use to find the type of company that would be the right fit for me.
After much resume redesigning, messaging recruiters from my failed phone interviews asking for feedback, and continuous learning I landed a job in New York at Squarespace as an internal controls analyst. Not a data analyst role, but the next best thing for me. Although I was still part of a finance team, I had to work closely with the data engineering team to give them our system requirements that they would build out. I was moving myself closer to my end goal.
I eventually would test these systems, on our end, and would have to put in a ticket if something was wrong. I took this as an opportunity to dive into the data and try to figure what was wrong on my own. Whether I was right or not didn’t matter. I entered not just the error, but also my assumptions. Sometimes I was right, a lot of times I was wrong, but I learned every time. I was gaining real job experience.
After being at Squarespace for almost two years, I built a lot of contacts within the data engineering, analytics, and science team members. I learned a lot from them and they guided me better than any article could ever on how to continue my learning path. Eventually I started applying again around New York at different tech companies for an actual data analyst role. Lo and behold, I had a few interviews this time! Unfortunately, I was rejected every time due to “not having enough experience” when compared to other candidates. I offered to work on a temp basis until I could prove myself, and I was asking below market rate. I just wanted to get my foot in the door.
One day I got lucky. My brother told me that a Ohio fin-tech start-up, Root Insurance, had some data analyst positions available on their career site. I didn’t think much of it at first. I applied just like I did to all the other listing that taunted me. After a month, I got an email asking for a call! After my call with the recruiter I did a little online stalking of the hiring manager and it turned out he was connected with my cousin, small world! I gave my cousin a call, and he had a conversation with the hiring manager. I’m not sure how the conversation went, or what was said, but I can only imagined it helped.
I submitted a work sample, and interviewed in person, and they said I was the best candidate that they had come across, I was blown away. It was actually happening! They extended an offer and I accepted.
Long story short
That was a lot to chew on, but the main points from are anecdote are as follows:
Know where you want to go. You need to know what you want or where you want to go, otherwise there is no direction. It took me awhile, but staying true to my passion of working with numbers as if they are puzzles, and a constant need to continuously learn led me to realize that a data analytics is where I needed to go.
Preparation is key. You can wish for all the dream jobs every hour of the day and it’ll do nothing. You need to learn what it takes to get what you want, and then start learning, training, practicing. Whatever it takes. This is why I paid for online courses and sought out professionals. I needed to prepare on all fronts.
Be physically present for incoming opportunities. For every thing I wanted, I made sure I was moving towards the right place. From UAE to Texas to New York. I went where I figured the next opportunity would lie.
Be patient. It’s tough, I know. Getting there is more than half the battle, and every step you take towards your goal is a new skill, new thought process, more knowledge that you gained. You succeeded simply by trying, so keep at it. You have nothing to lose.
“A smooth sea never made a skilled sailor” — English proverb
It may seem lucky that I happened to get a job as a data analyst where my cousin was friends with the hiring manager, but the thing is you probably already know a friend or family member that knows someone in the field you’re looking to get into. The only difference is that I was well prepared to take that opportunity and capitalize on it. If I didn’t learn SQL and Python, partnered with data engineers, analysts and scientists, kept re-tweaking my resume for every role I applied to, I’d be woefully under-prepared to interview for this opportunity, whether my cousin gave me a leg up or not. It took me around two years to get here as a data analyst, and perhaps it’ll take another two years to become a data scientist. Until then I’ll keep preparing until my opportunity arises.
Happy learning!
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