How to keep your skills sharp while data science job hunting
Video: Strategies for reaching out to companies
Good morning!
This is the SharpestMinds newsletter, where I share
A data science job search tip,
An update from our internal Slack group, and
A quick high-five to a mentee who’s just been hired.
The video: company reach-out strategies
If you’ve tried applying to companies by submitting your resume online, you know that usually doesn’t work. If you’re a mentee, you know all about the our cold email playbook that usually does work.
But apart from cold email there are a few other strategies that might work for you, depending on your personal context. I explore some of them in this video:
On to the Slack update!
The Slack update: staying sharp while you apply
Jiri Stodulka asks:
I’ve been focusing on the job hunt for about two months — and as a result, I haven’t done a lot of coding in that time.
I was doing some EDA yesterday and I was shocked to discover that I had to Google everything to get it done — I’d forgotten a lot of the syntax.
How do you deal with this issue? How much do you code these days — assuming you’re actively job hunting?
Jeremie Harris’s answer:
I usually recommend separating your week into something like 2 days’ skill maintenance and 5 days’ applications and projects when they’re hunting actively. But it varies from person to person.
One common way to divide it is to do project work on weekends, and job applications and interviews on weekdays.
Russell Pollari:
Yes, the solution is to explicitly schedule time to code. The right schedule for everyone will vary.
If the weekday / weekend split doesn’t work for you, one great approach is to do a minimum amount of coding every day — like 15 minutes — and scheduling it at a specific time. This is a kind of personal habit trigger called an implementation intention.
Karthik Subramanian’s answer:
I actually spent quite a bit of my time in this state before I got hired. I was juggling a full time course load, personal projects, and job search.
Along with semi-regular practicing, what helps a lot is documentation. Anything you practice, you need to document.
It’s not enough to practice to code. You should document your work well enough that you can look back and immediately go, “Yeah, I sort of have an idea how to go about this.” I remember doing a ton of problems on LeetCode for example — and a lot of the work went to waste when I wanted to revise it for an upcoming interview, because I hadn’t bothered to document my solutions.
Documenting stuff also gives you an easy way to look things up without relying on Google Search in that moment, as you’ve already done the hard legwork. I like to add the best link or two that helped me move quickly to the solution, so it’s much faster the next time around.
Drew Lehe:
I thought I was the only one who suffered from this! I always keep in mind the “forgetting curve” — so I spend more time coding than applying to jobs:
The hire: Max Pechyonkin 🙌
Finally: big congrats to Max Pechyonkin, who recently got hired as a Machine Learning Engineer at Fathom Health! 🎉
Max’s story reminded me just how effective a good cold email is.
Max arrived in Toronto from China just a few months ago. He had no connections at all in the city when he landed. He was able to find a great local mentor who helped him network, but they way he found his job at Fathom was from a cold email, sent straight to a hiring manager. Congrats, Max!
Here’s the full announcement on LinkedIn.
Have a great week! ✌️
— Edouard