https://ift.tt/3qZZo11 Break into data science without losing your money and marbles Photo by Sebastian Herrmann on Unsplash So you w...
Break into data science without losing your money and marbles
So you want to become a data scientist? But you have unrelated or loosely related experience? If that’s the case, this is probably not the only article you’ve read that tries to tell you how to become a data scientist. There are hundreds of articles and lists telling you what you need to be studying to gain the skills of a data scientist — so this post isn’t for that. In fact, if you ask the internet how to become a data scientist it’s likely you’ll get a list of classes and topics, be told to study them for 5–8 hours a day for 5–12 months, network, and then wham bam become a data scientist.
Ok, that’s a simplification. Still, I maintain there’s tons of bad advice on how to transition into data science. Lots of it promotes practically full time study schedules and neglects that…
- Most people have bills to pay and can’t afford to study full time.
- Working a day job and then studying for hours every day will lead to burn out for most people.
- Data scientist is generally a mid level position that demands some tangible, related work experience regardless of your knowledge.
So where does that leave you?
Well first, you’re probably not going to become a data scientist in 6 months unless you’re already a working engineer (software or otherwise) or mathematician. And that’s fine! It will take longer than 6 months but you also don’t need to study every hour of the day while you work towards your goal. What I’m recommending is to not study exclusively to become a data scientist but to get involved in data and get paid to learn the data scientist skill set as you work your way up.
So what makes me qualified to rant about this:
I’m a working data scientist on a team developing and implementing advanced models and have been in this role for about 6 months. I graduated from college in 2019 with degrees in Economics and Political Science, only really became aware of data science as a field my senior year, and set about aiming to become one a few months after graduating. I don’t claim to be the best data scientist but I’ve successfully set about going from minimal experience to a full time role which is what I imagine you’re looking to do.
I graduated without a job lined up so I set up one of those ambitious self study curriculums and threw myself at it. I enjoyed the learning process but I quickly ran out of money. I got a part time job which just burnt me out. I didn’t feel I was moving rapidly closer to my goals and I was growing concerned with the lengthening gap in my resume.
So what to do instead:
My luck turned around when I decided to set my sights on a data analyst job. There are far more entry level analyst than scientist jobs and studying up to a point of competence in the analyst skill set is a faster process. SQL is the critical skill, but for entry level jobs you don’t need to be an expert. Knowing the basics of select, where, group by, the joins, and case when should suffice. I actually studied with one of those “Learn SQL in 4 hour” videos the day before my interview which proved sufficient. Any Tableau or PowerBI knowledge is a great bonus, as well as being easy to pick up the basics, so if you have that you’re in a good position.
A search of entry level data analyst positions in the United States on LinkedIn yielded 53.4k postings while searching for entry level data scientist positions resulted in only 44.1k postings, many of which require 2+ years of experience, at time of writing.
I got a job as a data analyst for a medium sized e-commerce site and that analyst job changed everything for me. It was so impactful because now I could get paid to learn and I was logging time in a data driven organization that could go on my resume.
Of course if all you had to do to become a data scientist was become an analyst and add time you probably wouldn’t need to read this article. You will still need to self study your usual python, stats, machine learning skills because the analyst skill set does not totally overlap with the data scientist skill set. You likely won’t be doing much modeling as an analyst but you get to work with data every day. Data scientists need to be able to query data, decipher messy data, engineer features, and create visualizations which are all well in the analyst skill set. So in becoming a better data analyst you will become a better data scientist, and the growth you make in your time working will reduce the burden on you in your personal time. Additionally, being part of a data team will expose you to growth opportunities. I expressed an interest in developing modeling skills to my managers and because of that, I was able to assist in building a segmentation model for the company site despite being an analyst.
If you self advocate and continue studying data science you might be able to advance from an analyst to a data scientist at the same company but that was not the case for me. Instead I leveraged those analyst skills I had developed to join a rotation based analytics development program. I actually took a little bit of a pay cut to do this but I knew that I could rotate on dedicated data science teams and eventually land on one full time. I did two 3 month rotations where I was able to basically learn those data science skills 40 hours a week while getting paid and then got to join a data science team as a permanent addition. This is not actually where I am now, as despite working as a fully functioning data scientist I was not paid or titled like one since I came through the rotational program but with the experience I had accrued I was able to get a job with a big pay bump as a junior data scientist for another company in the same industry quite quickly.
The time between starting my first analyst job and starting my first fully titled data scientist job was a little under two years. Two years is nothing to scoff at but if you aren’t already working in a data science adjacent field, I don’t think you can expect to make the switch much faster without a Master’s Degree. MAYBE with some super human dedication you can make those intense study regimens work for you. And maybe my route was slower, but I…
- Never lacked for income.
- Progress I made at work meant I could study more at my leisure at home. This helped me recover from previous burnout and left me time for my other hobbies and social life.
- I got to interact with many smart people working in data science that gave me great advice and references.
- The work experience I had was critical to me getting my data scientist job.
If you’re switching to data science from an unrelated field try out becoming a data analyst first, even if it’s just a stepping stone, it’s a great way to keep moving forward instead of collapsing under the pressure of expecting to become a data scientist right off the bat and ultimately that makes it the easy way.
Start Becoming a Data Scientist the Easy Way in 2022 was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.
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