Create an account to participate in the community.

Sign Up Login

Question:
How can I get into a Data Science program without a STEM background?
Asked on 2020-11-23 18:51 by Roberta U.

I have an undergrad in history and politics, and took a few sociology classes where we discussed survey methods, basic stats. I don't know how to write code or do anything fancy from a machine learning perspective. Is it possible for me to get started in this space?

Response #1
By Wojciech G. on 2020-11-23 19:03
We get this question a lot, and I wanted to throw in a brief "guide" on the topic.

  1. Emphasize your subject matter expertise. I believe in the concept of “hybrid data scientists”; these are individuals who have a huge range of experiences or work backgrounds, but they might not be in formal STEM areas, or maybe not in data science. The intuition you build up in these other areas can be framed as a huge strength.
  2. Be practical with your data science capabilities. Tell the story of how your strengths can be used to support your data science ambitions, or the broader data science team requirements wherever you're joining. Many data scientists aren't great visual designers, some struggle with written communication, others with customer service... I ran a company called Canopy Labs a while back, and we would hire customer service reps who we'd train in data science. They would be great communicators and in 1 or 2 years, would move into data science roles due to our training!
  3. As you get more experienced, build a portfolio that pushes your skillset and illustrates your (new) capabilities. Data scientists, analysts, and other data professionals who are serious about their careers need portfolios. It shows you can do end-to-end projects, and speaks louder than any resume item you have.
Let's summarize the above... Imagine you're someone who has retail experience (e.g. working as a cashier or in a retail store). You understand customers, you might be good with people, and you understand the "on the ground" challenges of a retail environment better than many experienced data scientists. You can present yourself as someone who is a subject matter expert.

Building a portfolio with retail data (e.g., from the BLS in the US) could showcase how you understand the on-the-ground retail situation while also being able to analyze data. That's powerful!

This is a great question and I'm happy to help further!

Lola O. on 2020-12-30 03:45:
Thanks for sharing this. I am still crafting my personal career story in such a way it will align well as a Data Scientist/Data Analytics.  Trying to put all my pieces together. 
Wojciech G. on 2021-01-01 21:38:
Good luck, Lola! Feel free to share your portfolio or story in this forum and we'll try and get you constructive feedback.
Response #2
By H L. on 2020-11-25 18:38
I would also add that as you focus on your DS careers, from a tactical perspective, look to the jobs that will provide a good stepping stone. look for DS roles, but also look at analyst roles (business analyst, report analyst, product analyst, marketing analyst). Within reason, anything with an “analyst” job title may give you great exposure to real life, messy datasets, and you can use that as leverage to further enhance your skills.

From an employer perspective, depending on where you are, consider the smaller firms.  Those may not be as competitive and will  have more leeway in you trying different tasks.  

I came from a non-tech role and I got my first job merely because the company was small, and after I got rejected, I emailed the hiring manager 3 months later and was like “Hey, I’m still available if you ever need someone”, and either he/she appreciated my grit or just felt a bit of pity, but 5 years later, I’m now at a new place that I really enjoy.  It definitely takes a lot of determination, but also some luck, so don’t give up!  Just have a plan and have a good survey of the market, and also your own capapabilities (strengths, weakness, etc)

Wojciech G. on 2020-11-25 18:51:
WOW! That is such a good story. Kudos on the follow-up strategy... I think too many people lose hope and don't build good relationships with companies and hiring managers.
H L. on 2020-11-25 23:38:
Yes!  I honestly don’t think it will work every time,  but I think the stars just aligned and the rest is history 
Andrea Y. on 2020-12-30 03:50:
I love that you didn't give up :) Persistence is omnipotent.