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A quick background
I graduated back when data science was still not as strong of a buzzword as it is today. Many of my peers either went to consulting, banking, medicine, or some other traditional job in industry. I didn’t have that many friends who went to Big Tech.
Many of my peers have worked in analytically-heavy roles: think business analysts, operations, marketing, non-profit, etc. Many of them have played with Excel, and some even taught themselves SQL and Python. So their skills naturally translated to data science roles.
Now, after a few years in industry, many of them want to move to a "data science" position at a startup or in Big Tech.
I don’t blame them.
Data science positions in tech pay a lot more than the previous roles that they were in. It can be at least a 50–100% increase in their pay, if not more (I know salary is taboo and all, but especially if you’re in the US trying to get into a role in San Francisco, let’s not kid ourselves).
I actually went through this process myself, going from a consultant at a Big 4 accounting firm to a data scientist at FAANG, all while COVID is happening (that’s for another story). When I started reading advice from blogs, articles, etc. about how to break through, I got intimidated.
"I need a Master’s"
"I need to start over in my career"
"I need a profile full of green boxes in my GitHub portfolio"
Advice that was well-meant, but for my specific situation, totally irrelevant, and if anything, stopped me from taking action.
Thankfully, I pushed through those fears and eventually landed on my current role, which, for full disclosure, was about a 510% increase in compensation for me. Let me share with you what I learned throughout that journey.
Who is this for
If you want to go to a specialized field within data science (e.g. computer vision, natural language processing, data engineering, research science), this is NOT for you.
This is written specifically for those who are working in some capacity as an analyst wanting to break into tech (Big Tech, startups, or anywhere in between) in a data science role, basically, those like my peers back in college.
When I was applying for roles in data science, these were the most common concerns that I had. I also asked my friends about them, and they shared these concerns too.
I’ve anonymized the quotes below for privacy’s sake.
1. I need a Master’s Degree or a Ph.D. to get a job in data science

"As for improving [my] candidacy, most roles I last saw needed more experience. Do you think a Masters in Analytics would help?" – Nishant
"Am I gonna have to take another Master’s again?!" – Jingrui
Response
You need to know what type of data science role you are applying to, and what type of role you’re coming from. Unless it’s a research-related role, a master’s is almost NEVER required. If you’re already coming from a role that uses analytics in some capacity, then unless you want to do research, you only need to brush up on technical skills to get in.
You may see some non-research data science job posting that requires or prefers a Master’s or Ph.D., but it’s not a strict requirement. Heck, I landed a role as a data scientist that specifically stated "Master’s or above", but I only have a Bachelor’s degree (see question 2).
Otherwise, if your current role has nothing to do with analytics, then a Master’s can be one of many options.
My suggestion, however, is to find an analytics-related role that may or may not be your ideal role. Not only is it cheaper than a Master’s (which as of this writing can cost $40–70,000 a year), you will gain valuable experience, which employers value A LOT MORE than your academic background.
2. I don’t have the experience

"Sometimes it feels like a catch-22, it seems like a lot of these companies want experienced candidates, but it’s tough to get experience without getting into a good position first." – Abi
"Companies expect way too much from a candidate who is trying to break into data science. Also, there are very [few] job postings for entry level data science roles." – Sashank
Response
If you’ve been in industry for a while, find out what skills you already have that transfer to a data science or analytics role. Remember that job descriptions are more like wish lists and not about hard requirements.
For example, I wanted to switch from a Project Manager to a Data Scientist for a Big Tech company. Here were some of the requirements for the role:
- Apply statistical methods, develop A/B tests, and automate data pipelines to develop metrics
- Work with engineering teams to improve data collection
- Master’s Degree or above in Computer Science, Statistics, Mathematics, or other related analytics disciplines.
This is what I had on my resume:
- Designed and A/B tested display ads across 6 customer segments to increase marketing conversion from 1.5% to 3.2%, decreasing marketing costs by 49.2%
- Built an automated Python pipeline to alert which retail stores need more stock based on metrics like week-of-cover and weeks-to-sale
- Bachelor’s Degree in Mathematics
Even though I didn’t have all of the "strict" requirements that they were looking for (I only had a Bachelor’s), I was able to apply to roles like these, get final round interviews, and landed this specific role, increasing my income 510% (that’s not a typo, I 5.1x-ed my income)!
3. I need to come from a good school

Response
No, you don’t. Unlike consulting or finance, where good name schools are valued, especially for Big Tech companies, they care a lot more about your skills and experience than which school you graduated from.
See Question 2 regarding experience.
4. I don’t know Python, SQL, R, Spark, Hadoop, Tensorflow, or [insert technology here]

Response
Focus on the one skill that you know best and use that in your interviews. If you know more than one (say SQL and Python), make sure you’re consistently using the same one for your interviews.
If you don’t have ANY of the skills in the job description, dedicate yourself to ONE and start there.
When I started out, I didn’t know any programming languages. However, as a Project Manager, I taught myself Python on the side (think Datacamp, Dataquest, Udacity) and even asked my boss to be involved in a couple of Python projects on my own.
I put myself out there and created an opportunity for myself to be proficient at Python. Now, I can apply to jobs a lot easier. You can do the same thing!
Start looking for ways for you to work on your technical skills at your current job. If you can’t find these opportunities, look for another role that will enable you to.
5. I’m not getting replies from companies

"There are so many communication delays. It takes them at least two days to get back to me… the process is slow and really elongated. Honestly, if they’re just upfront with what the timeline looks like, [if they tell me that] I got rejected, I can then focus my attention elsewhere." – Fan
Response
Before you even start sending out resumes, make sure that you’ve done your homework. Talk to the data scientists in the roles and/or companies that you’re interested in. Understand why they are recruiting for such roles. That way, when you start talking to recruiters, they will feel that you know what you’re talking about.
Also, as a PSA here, please be nice to them. Many of these recruiters aren’t even full-time employees, work 50–60 hour weeks, and work on weekends. Imagine getting 10 follow-up emails from this "persistent" (more like annoying) candidate asking for a job. Probably not going to go well.
Both of these will increase your chances of getting replies back, but not everyone is going to reply to you. At the end of the day, it’s still a number’s game. Maybe you email 10 recruiters, only 1 or 2 might reply back to you.
Maybe you and the recruiter just didn’t have good chemistry, or maybe the role already got filled but they just were not able to notify you. Remember, they’re busy! Don’t put all your hopes and dreams into one company. Just move on.
6. I need to know someone inside the company to get an interview

"I use LinkedIn to invite them for coffee chat[s], but there’s still a gap because [it’s between] strangers. Having a network through your alumni or past jobs really helps, [especially when there is an] opening in [their] team or organization." – Jade
Response
Maybe. The short answer here is that you should take advantage of whatever connections you have, but they will NOT guarantee you anything. Whether you get it via a cold email or through a warm connection, you still have to prove yourself to the interviewers.
I actually got to the final rounds of an interview without knowing anyone from that team or department.
When I was applying to a data strategist position for a business development team, it was already at the closing stages of the interview process. I reached out to the recruiter for this position, and when I called him, we really hit it well with each other.
He was so impressed with my skills that he went out of his way to shortcut the process for me, skip the technical screens, and convince the hiring manager that she should do a final round interview with me for the role.
I ended up not getting the position, but the lesson here is that, it’s not necessarily about who you know, but how you treat them.
Remember, I did NOT know the recruiter personally or had a secret back-door connection. I built rapport with the recruiter, showed him why I was a good candidate, and followed up with him courteously.
7. I am too old to switch

"I feel like I don’t have that edge anymore unlike when I was in college. I was surrounded by so many high-achieving people but now I feel like I’m slowly degrading." – Philly
"I know that I need to go [somewhere better]. But with me having to support my husband, I feel like it’s risky for me to switch jobs now." – Lakisha
Response
It’s really hard making a switch, even though you know deep down that this is the career path that you want to take. And of course, if you have commitments to your partner and/or family, then those also need to be taken care of.
Having said that, it’s never too late to start something new. Especially in a field with so many new developments, there will always be a place for you to grow in your career and still be able to support those who rely on you.
To make this transition easier, I suggest talking to someone who recently switched into data science and is in a similar position as you are, and connect with them. If, for instance, you’re a newlywed who is looking to make the switch, finding other newlyweds helps you not only with better connecting with them, but also giving you practical advice on more personal matters related to being newly wed.
And there you go! Based on my own job search experience, hopefully I’ve been able to address some of your major concerns when transitioning into data science.
If you want to know more about my backstory and how I landed my dream role in data science, subscribe to my newsletter here.
Edit: Fixed some formatting issues and typos.