It is very clear that data is changing our world, from medicine and agriculture to manufacturing and gaming.
In this article, I offer my advice on how to get a job that allows you to become a part of that change as a Data Scientist.
Just a quick side note for you to remember as we move through this article:
This is my own personal opinion. As with all advice, it must be taken with a grain of salt, particularly when dealing in such broad terms i.e. not focusing on a particular industry or specified role.
Every hiring manager has different opinions or preferences. For example, I personally don’t like cover letters, mainly because in order for a cover letter to be effective it must be personalised. However, how can it be at the early application stage?
On the other hand, another hiring manager might not even consider an application if there is no cover letter accompanying it. This is not to say that one of us is wrong or the other is right. It’s just my opinion and I am entitled to it just like you reading this post.
Okay so let’s get into it…
Typically the first step for a Human Resources department when beginning their search is to first post a job listing live on a website. From there what happens next is there is an immediate spike in applications.
That will then trickle off and there is a long tail of it. Generally, at some point, that listing is cancelled and re-posted in order to trick the algorithms to make it look fresher and so on. It is important to remember that everybody in this chain is playing a game.
A lot of these platforms have different scams and schemes on how they make their revenue. Of course, they are obviously trying to turn a profit. It’s business. This means that they are highly incentivised to lower the quality and increase the volume of job listings.
It’s not necessarily a villainous thing to do though. Maybe a hiring manager wants more applications in order to scrutinise more, whereas a busier person might want to see less and more highly targeted.
Every business looks at their business in terms of a funnel, their customer base. You should try to apply for jobs using these same processes. You might need to bear with me here for a short time, but I promise its all connected…
We will use an e-commerce website that are selling t-shirts as an example, something basic. Their first job is to get you on the website through advertising, email marketing etc.
Next, How many of those people put something in a cart or registered an account? Track it. What percentage did it? How can that be improved?
Repeat those steps from cart to checkout process, not completed order because maybe the storefront sucks. How many people actually get to let us conclude an order? Enter credit card details? Adjust accordingly.
From there you look at what percentage actually convert – Conversion. Then repeat rates and so on. You get the idea.
How do companies manage this process?
Well typically depending on the budget, a company will buy traffic from a number of sources and then follow them through. Does traffic from any of those sources convert higher at a particular step? Why?
I believe that this same conversion funnel can be applied when applying for jobs.
Application to video/on-site interview conversions?
It is obvious every company is different, but there might be more than one video interview or they might ask you to complete a mini project. Something to that effect.
What percentage of your applications actually converted to a phone interview? If this number is low, you know something is not right. Just like in business terms you might need to adjust accordingly i.e. the way you structure your applications.
If the conversion rate is really low then it might be a good idea to go back to the drawing board. Do more research. If you are successful with your video interview, then typically the next step is an on-site interview. Meet the people, spend maybe a half or a full day there.
Again, know your numbers. How many of those on-site interviews converted to actual offers? If that number is low, then maybe you need to look at your interview preparation etc.
First rule; Don’t be annoying. Its important to remain professional with your follow up in between stages. Know who it is you are contacting and what their role is.
For example, HR reps are people that you shouldn’t mind bothering. It’s their job to make this process efficient and cost-effective.
However, if you’re talking to someone who might be your supervisor or a similar role, they might be a busy person; It’s probably not a good idea to bother them. This is not their job.
Don’t be a spam artist.
Sending the same resumé to 10 different companies is just a waste of your time. Particularly for graduates or people with very little experience. Personalise and optimise your resumé for the role you are applying for and the company you are applying to. Do your research and put the time in.
Know as much about the company as you possibly can. If that company produces podcasts or hosts meetups, be sure to know about it. Try to show a general interest in what they are doing, be genuinely interested in the company you are applying for.
Find out who it is your talking to on the phone screening. Is it a technical person or a HR person? Research their LinkedIn. You may be asked some stock questions.
These are questions written for the interviewer, usually by a data scientist. Below that are some bullet points containing data scientist phrases and terminology that they are looking for you to hit. Make sure you hit them.
The same goes for your resumé…
It is likely your resumé is going to be reviewed by a person who is just looking for some basic keyword stuffing that they were trained to look for. Make it clear and organised.
If you don’t then the person reviewing your resumé may just dismiss it right off the bat. Again, another waste of your time.
Send a PDF, do not send a Word Document. You have no idea how that is going to open on somebody’s computer.
Have a GitHub link, it’s very important to showcase your skills as a data scientist.
So if the interviewer is a technical person, their job is to take a measurement of the technicality of your language. Assessing how you communicate in technical terms. If you really know your stuff as a Data Scientist, be confident.
Do not put stuff on your resumé you know nothing about. At this stage particularly is where it could be your downfall.
Just one final note for all the data scientist graduates out there…
Don’t just list your classes and GPA. Focus your enthusiasm and what you have learned into an area you are really interested in.
If you want to work on Image net and transfer learning? Great. Go learn some Tensorflow, use some of those vision API’s to make a little project. Build something.
If you follow the guidelines I have outlined here, you will find greater success when applying for data scientist jobs.