Getting Your Foot In The Door
I asked you guys what you currently work as. You guys responded. Now here's a strategy on how you should slowly get your foot in the door,
Appreciate everyone who told me what profession they currently worked as. Unfortunately, I had way too many responses, so I had to miss a few.
Note: You should always be applying for a data scientist/machine learning engineer role, regardless of where you are on your journey. Worse case scenario nothing happens. Best case scenario, you get lucky and land an interview which converts…
I’ll be using the DS, and the MLE acronym quite a bit.
Here’s what they mean:
DS: Data Scientist
MLE: Machine Learning Engineer
Objective: When a hiring manager looks at your resume, we care about things that show your competency with Machine Learning, Data Skills, Python/R, and SQL. Take a look at the below tweet:
Methodology: The goal is to use your current role, and see if you are able to grab relevant skills on your resume. For example, if you come from software engineering, you already got Python covered. We need to get your ML & data skills up. If you come from being an art teacher, you’ll want to snort acid.
I’ve categorized all the roles I saw in 3 major categories: Easy, Medium, and Hard.
If you have not read the post on fixing your resume, and how to prep for interview. Stop… and go read those posts first!
Table of Contents
Easy
Medium
Hard
1 - Easy
If you are in this section, you can grab the SQL Certification (1Z0-071) if you wish. It’s a nice resume booster, but considering you already have a lot of relevant work experience, you don’t need it.
Research & Development Scientist
The odds are you are familiar with concepts such as: supervised/unsupervised learning, data cleansing, and you already have some technical skills.
In your case, you have already done the difficult part, you were able to grab a relevant data role.
The next step is to start focusing on Python, R, and SQL until your skill with them are solid, and you can pass interviews. Once that’s done, apply for a data analyst role (if they use R/Python & you don’t have this skill on your resume yet). At that point, you have a solid foundation, and you can transition to a DS/MLE role.
Your best bet would be some sort of a data scientist/analyst role that is focused on research side. This is because you already come from a research heavy background. Machine Learning Engineer will be a bit more challenging to meet.
Note: The biggest hurdle will be improving your technical skills. Researchers are generally known for having mediocre tech skills.
Data Science Intern (Unpaid)
You already have a data science role on your resume. Ping them again and ask them if you can continue to work when the school term resumes. Also, ask them if you can transition to a paid role since you’ve proven yourself.
If they say yes:
Great problem solved, then ping them again to ask you can work with them full time
If they say no:
Who cares, you already got a data science internship on your resume, work for a different company. Not a big deal.
Software Engineer
If you come from a Software Engineering background, you already have extensive experience in writing code in Python. Take a look at the similarities between a software engineer and a machine learning engineer below:
Depending on where you worked, you may have SQL skills, or you may not have them.
If have SQL work exp:
You’re ready
If don’t have SQL skills/work exp:
Learn SQL, then grab the SQL certification (1Z0-071) to show your competency.
At this point, the main thing you are lacking is some real hands on work with Machine Learning. To remedy this, you should work as a Software Engineer for a company where the ML Team, and the Software Developers work hand in hand.
Usually, this will be done at the API level, or they’ll be working with similar servers. It’s here where you will want to take on more ownership over projects that deal with the ML team, until you can transition to the team. Welcome aboard.
Note: A lot of Machine Learning Engineers transition to Software Engineering, and vice versa.
2 - Medium
If you are in this, you NEED to get the SQL certification (1Z0-071) on your resume, it’s not optional.
High School Math Teacher
If you are in this role, the only relevant skill you have is your knowledge on highschool statistics. That’s about it. Because of that, you are in one hell of a tough time.
You need to start learning SQL, and prepare to grab the above mentioned SQL certification. That is your number 1 priority above all else. Once you have attained it, you need to grab some SQL related work experience position. There’s plenty to pick from:
The most likely one you’ll grab is either in analytics, or a SQL Database Administrator. Then, you’ll want to learn Python/R. Once you’ve done that, you’ll want to use the prior SQL work experience to transition to a data analyst/junior DS role (pay will be awful).
Spend a few months here, and you should be able transition to a proper MLE/DS role.
Due to your math teacher work experience, you don’t need to spend any real time learning the mathematics. Read up on the law of large numbers, and why data professionals care about it, and you’ll be fine.
SAAS Implementation Manager
If you come from this background, you have some levels of IT skills. The odds are you most likely have some prior work experience with SQL. That’s great because you have an important technical skill mastered, we need to swap you to a more relevant role.
Since you come from a more technical IT side of things, you’ll have better luck transitioning into a more production/IT focused side of SQL. Good roles to look at would be database administrator, SQL architect, production database tester, etc.
From there, you’ll want to start picking up on R/Python, and some data skills. If you are lucky, you’ll end up in a IT role that works right next to the data team. Then, you can start working closer and closer with them, until you join them outright.
If you are not lucky, then you’ll need to have a temporary role as a data analyst for a short amount of time. You'll then leverage this to get into a data scientist/machine learning engineer role.
Note: You can even go into a data engineer role if you wish, since you come from an IT heavy background.
Finance Assistant
The first thing you need to do is learn Python (skip R for now). You’ll want to use Python to automate a lot of your finance/accounting tasks. Congrats, you turned an irrelevant work experience into a relevant one.
Once you’ve done that, and put that on your resume, you’ll want to grab the SQL certification to prove your SQL skills. You’ll want to leverage the two together to land some sort of a relevant Python/SQL work experience. There’s a bunch of them so pick whatever:
From this, you can jump into a data analyst role, or if you are *really good*, jump straight into a machine learning engineer role.
3 - Hard
If you are in this, you NEED to get the SQL certification (1Z0-071) on your resume.
Sales Development Representative/Manager
First, we make sure we don’t follow garbage advice like this:
In your case, you have a solid ability to communicate. Unfortunately, most of the people who work as a DS/MLE are on the autistic side. This means they don’t care too much about your communication skills. They care far more about your technical skills.
In your case, you are starting from scratch. The best thing for you would be to grab the SQL certification. From there, you’ll want to grab a role (any role) that focuses on SQL. Here’s a few good candidates:
You can start learning R/Python. I’d also encourage you to grab the certification for Tableau or PowerBI (you desperately need a data analyst role). Then, you should be able to land a data analyst role. From there, it’s pretty easy slingshot to get to a DS/MLE role.
Waiter
You my friend are fooked. You have literally 0 relevant skills. You don’t have math, Python, R, or even SQL skills if you work as a waiter. Here’s how we’ll fix that.
The first thing you should do is ask your manager/owner of the restaurant if there’s any tedious data entry, or something similar that you can help out with. Usually they’ll say entering receipts is a nightmare.
From there, you’ll start learning Python, and get a solid understanding of the tool. Once you’ve done that, you’ll try to solve his above problem, and put your Python skills to the test.
The reason we do this is because it’s much easier to land a relevant role if you already demonstrated your skills prior hand. Ain’t no one taking a shot on an adult who has absolutely 0 relevant work experience (different story if you are student).
From there, you know the drill → grab SQL certification → grab a role that uses Python & SQL → jump to data analyst → become data scientist/machine learning engineer.
Military
See if you can grab the SQL certification asap. Once done, grab a role that uses SQL, then teach yourself Python (skip R for now, you are already time constrained). Then leverage that to get into a data analyst role, and should be able to become a machine learning engineer.
Getting Your Foot In The Door
I'm a reply guy on titter how can I become data scientist