The Resume with which I Got My First ML Internship in Canada
How to get a job in machine learning? My personal story
You’ve probably seen a lot of articles with this title. Each person’s experience is special, and you can get a grain of useful (and at the same time unique) information from each personal history.
Nevertheless, most of the articles on this topic that I came across sounded a little strange to me: one of the resumes in such an article consisted of two pages and the second page was literally a list of scientific publications and patents (wow, impressive!).
2023 update.
A year later, some things have certainly changed here. Most of things in this article are still true, but I should also have said about the importance of a good questions, cover letter and of course referral if it’s possible, but this is a separate (and big) topic. I also think it’s better not to use the tabular resume format that I use here because apparently (but not certainly), it is worse recognized by the Application Tracking Systems and other software.
Remember that it is more a personal story than professional advice since I don’t have professional experience in the job hunting field. When writing your resume, review information from many sources, and it is best to ask for advice from experienced people from the industry. With this in mind hope you will enjoy the story and good luck in your job search!
TL; DR
How is my story different from all the previous ones? Well, if I don’t have the worst resume, then probably one of the worst, at least in two main fields:
- Education — I’m a Bachelor of Computer Science from a city you never knew about;
- Experience — I have almost no relevant work experience.
However, I was able to find a machine learning related job in Canada, although it was difficult and took a whole year.
Education
As I already said — I’m a Bachelor of Computer Science from an unknown university. Of course, by having a good education, you have a better chance of getting a job, at least because of the connections and networking you have access to. But if you were not lucky enough to study at a top university — prove that you deserve a job by other means.
Experience
I guess this is the most important point in your resume — where you worked before and how you can present the results of your work greatly affects your chances of getting a position. Nevertheless, everyone needs to start somewhere. This is the famous Permission Paradox or Experience Paradox: if all employers require employees with work experience, how to get this work experience?
I’m not really an expert in this matter, but that is what I’ve heard from many others: you can’t leave this field empty. It might be appropriate to list the university practice here and mention elaborate coursework or a corresponding degree project. But you can’t leave it empty. If things are really bad, you can look for an open-source project to contribute to or gain some volunteer experience.
Yes, Personal Projects (again)
Since my work experience is completely unimpressive, the data science/machine learning projects section is the most valuable and powerful part of my resume. And if you have a similar situation with work experience, you should have a similar situation with projects as well.
That particular section can let you get a job. It can tell a potential employer: “Hey, I don’t have any work experience, but I’m trying, and I’m trying hard!”.
You’ve probably heard this more than once, but if you don’t have any work experience, personal projects are vital to you. Make them as interesting and complex as possible, use modern technologies, try implementing something from scratch to get a deeper understanding of how a particular algorithm works, etc.
All this shows that you are interested, that you are ready to learn new things, ready to face difficulties and overcome them.
Are you really like that? Prove it!
Here are links to my projects. I don’t know how much it helped that I wrote blogs on Towards Data Science, but it helped me first of all. Only by explaining something to another person, you can fully understand it. So writing tutorials or a personal professional blog is a very good way to start a data science career.
- Predicting the number of dislikes on YouTube videos: part 1 and part 2;
- Automatic Video Editing;
- Real-time “me-not_me” Face Detector.
Your level or interests may differ significantly, but you need to find something that will inspire you.
If you don’t have any ideas for projects, you may not be ready to implement them yet. To think and see the world in machine learning terminology you need a pretty serious knowledge base. Try to read another book or take another course to digest this knowledge and reproduce your own idea.
If you think that you are ready, but there are still no ideas, look for them on the Internet. Often the quality of such articles leaves much to be desired (you are advised to classify the iris dataset OR to solve some computer vision problem, although these tasks are of completely different levels), but this may lead you to your own thoughts.
Other Sections
Skills
Honestly, I filled in this section in such a way to list as many keywords as possible so as not to be filtered out at the very beginning. As far as I know, keywords search programs are used when selecting resumes, especially for beginner-level positions (e.g. intern or junior), because HR specialists can’t process them manually.
Also, it is important to remember that specifying skills that you don’t actually have is a bad idea.
Certifications
Here I have listed the courses from which I got the main knowledge about data science and machine learning.
I also think it doesn’t make much sense to enumerate:
- individual courses because the list will be too long and detailed; instead, you should list your programs/certifications;
- entry-level courses (like Machine Learning by Stanford) because your potential employer might think that your knowledge/qualification is insufficient.
Full Resume
Putting all the parts together, I got the resume that brought me my first job in machine learning, my first job in Canada, and my first good job in general. Thank you, resume!
Conclusions and Final Thoughts
Finding a job wasn’t easy. It took me a whole year to get one interview invitation. To be honest, I do not know whether I was unlucky all this year, or, on the contrary, I got lucky once.
While I was looking for a job, I often changed my resume, adding and removing some parts, changing formulations, or reorganizing the order of the sections. I don’t know which of these transformations were really successful, but here’s what I can say for sure:
- Don’t complicate your resume.
Don’t list all the projects in your life or all the courses you’ve taken. I think three is quite enough for an entry-level employee. - Do not strive to make a one-page resume.
This is my personal view and a piece of advice from several people I’ve talked to. All online services say that a beginner’s resume must be one-page, but you should not strive for it too much. - Don’t be afraid to ask for advice.
Do not hesitate to ask for advice — everyone started somewhere, and many (if not all) faced problems, so people usually treat this with understanding. Perhaps some friend or professor at your university can push you on a successful path. If you can’t ask for advice in person, use the Internet and the relevant sites/forums. Sometimes it’s just important to talk to someone when you feel stuck.
And finally: never give up. I sent more than a hundred job applications (and this is far from the limit) before I received a response. It’s hard to find a first job, extremely hard sometimes, especially for immigrants or people changing career paths. But the second job will be easier to find, and the third one will find you by itself.
So good luck. Perhaps you will receive the desired offer today! So make an effort to do it.
Thank you for reading!
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