For several years now I've been receiving emails from our data ninjas asking me the same question over and over: "What do I need to do to get my dream data science job?"
My answer has always been something along the lines of:
What I never said was "perfect your CV".
And that was a mistake, because - even though we're all about the technical stuff here - the technical stuff doesn't matter if your CV doesn't even get read.
So I'm going to correct that mistake.
Let me introduce you to a friend of ours - Kristen Kehrer of the Data Moves Me blog.
Whether I’m teaching a course, public speaking, or a guest on a podcast, what I most often hear is that people enjoy my energy.
I bring my passion to everything data.
Kristen Kehrer - Data Moves Me
If you hang around data science groups in LinkedIn you may have heard of her already, but if not, she is someone that you ought to be following.
Kristen has created a video course called Up-Level Your Résumé, and she takes you through the 7 most important steps to getting that highly-paid data science job you've had your eye on.
Let me briefly take you through the 7 steps before I hand you over to Kristen...
1. The Layout of Your CV
Have you ever heard of ATS, the Application Tracking System? Nope, me neither.
Well, as it turns out, the ATS is used to automatically manage applicants and their resumes. It reads your CV and extracts relevant information, like your contact details.
Here's the thing, though. If your contact information is in the wrong place on your CV, it won't be read and your application will be automatically rejected.
You don't want that.
Kristen teaches you exactly where to put all the important information so that your CV won't get rejected.
Think about that for a second. Getting this right means that your CV gets through and your competitors get rejected!
Those other guys might have hugely impressive data science skills, but they get thrown right out, while you get in!
Trust me - having this crucial information is worth the course entry fee all on its own!
2. Your CV Tagline
What is the first thing that gets read in a CV? The summary at the top.
What is the purpose of the summary? To showcase your prodigious talents? Highlight your education and experience?
The purpose of the summary is to persuade the reader to continue reading.
The reviewer might have 200 CVs to read, and if your opening line is a snore-fest, they simply won't read more.
Their purpose at this stage is to reject as many applicants as possible so they don't have to read 200 CVs!
Kristen teaches you to use a tagline rather than a summary, and shows you exactly what to put in there, what to leave out and how to structure it.
That's another 80% of applicants rejected, and you're still standing!
3. Data Science Skills
Now that you've got that killer tagline and the reviewer wants to read more, here's where you get the chance to persuade him that you really do have the coding and modelling skills to be an effective and efficient data scientist.
If you're like the rest of us, you won't have all the data science skills in the world, so how do you showcase your skills (and lack of) to show that you're a great candidate for this job?
This is what Kristen focuses on in this lesson. She will teach you how to match your skills and experience to the job description, even if some of your skills need a bit of a brush-up. Better still, she shows you how to explain how to make an area where you're lacking sound positive rather than as a weakness or a deficit.
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4. Data Science Experience
One of the most important skills that defines a data scientist is the relevant domain experience they have. It's just fine and dandy having logistic regression skills in business, but if you're applying for a job as a medical data scientist, they're going to want to know that you really do know your onions in the medicine department, and not just in business.
Kristen helps you match your experiences specifically to the domain in which you're applying, and teaches you how to add value to the job post by focusing on the benefits of your experiences rather than on their features.
So instead of saying 'I do logistic regressions', you should say something like 'I created a predictive model that increased efficiency by 68%, resulting in yada yada yada...'
You see the difference? 'Course you do...
5. Your Data Science Education
You have an education, right? And some experience. But what counts as 'experience'? And is experience worth more than an education? So should you put education above experience in your CV? And how much importance - and therefore space - should you give each of education and experience?
Kristen teaches you how to get the balance just right, and gives you insights into what employers are looking for.
Getting that dream data science job - why you need a resume tagline and not a summary #resumetips #jobtips #datascience @eelrekab @chi2innovations
6. Use LinkedIn With Your CV
You've got a nice, shiny CV that is trimmed perfectly to that data science job you're targeting. You send it off, then wait. And wait, and wait. You never get a reply.
Oh dear, something's gone wrong!
Maybe the reason is because the reviewer took the time to look at your LinkedIn profile and saw that it paints the picture of someone completely different to the person he sees in the CV.
In this lesson, Kristen shows you exactly how to edit your LinkedIn profile so that it matches your job application - giving you a real advantage over all those other schmucks who didn't do it!
7. Your CV Cover Letter
It doesn't matter how good your CV is, it's a statement of the past. And you know what they say... the past is not a guide to the future!
Ultimately, a prospective employer wants to know what you can do for them now and in the future. This is where the cover letter comes in, and it's probably more important than the CV (although if you don't get the CV right, they won't even read the cover letter).
The cover letter is the clincher and is what persuades the reviewer to pick up the 'phone and invite you to an interview.
In this lesson, Kristen goes through the most important details of your working life and teaches exactly how to structure your cover letter, how much detail to go into, what extra information should go here, keyword density and much more.
Your resume passed through the ATS of Google. That’s the important part and that’s 100% correct, honest and true.
You can also stress that I NEVER get any positive answer before. Just few automatic negative ones.
I am hoping to advance my career to the next level from being an Analyst to a Data Scientist, and I found Kristen’s course very useful and effective.
I will recommend this course to anyone who wants to have an effective resume as a Data Scientist.
That's not all, because throughout the course, Kristen has made it really easy for you by creating all sorts of cheat sheets and documents to help you with every aspect of building the perfect CV for that perfect data science job.
As you go through the lessons Kristen gives you:
And if that wasn't enough, you'll also get:
All in all, I think this is a great course, and I strongly recommend it if you're looking to level up your career and get the highly paid data science job that you deserve.
Go and check it out now!
UP-LEVEL YOUR RESUME
Transform your data science résumé into one that gets calls