Two weeks ago, for the first time, I whipped out my credit card and signed up with Medium.com – all to access just a single article.
For years, I’d successfully resisted that siren-call from Medium, keeping my access to the monthly minimum.
But this one … was a must-read.
A Bit of Backstory
For those of you who don’t know – I’ve been teaching in Northwestern University’s Master of Science in Data Science program for the past eight years. Over that time, I’ve created two new AI courses, completely revised another, and shaped their AI specialization.
One of the most important things that I’ve introduced – in EACH of these courses – was that each student would individually select and craft their unique Portfolio piece. (Of course, students could work in teams – but when they did, it was because THEY decided to; not because I was arbitrarily shoving them into team projects.)
This emphasis on Portfolio-building has been a hallmark of my teaching … for years.
And now, there’s this pop-up post on Medium.com that says … maybe this isn’t the most important thing?
Aaagh!
I had to find out.
Hence, the credit card.
Summarizing the Author’s Key Point
I won’t do a complete give-away of the points made by the author, Haebichan Jung. (See full citation in the Resources and References, at the end of this post.) Suffice to say that the key insight that he shares is a quote from Jeffrey Li, at that time with DoorDash (and now Sr. Data Scientist with Netflix):
The biggest pitfall I’ve seen in most Data Scientists on the market is being able to connect the machine learning model to the business impact.
Jeffrey Li, being interviewed by Haebichan Jung.
Here’s the YouTube vid of that interview.
So here’s our key take-aways from Haebichan’s YouTube and Towards Data Science article:
- Projects alone don’t get you a job.
- Immersing yourself in a project-focused strategy, with the assumption that people (i.e., hiring managers) will have time (and even the interest) to read your code, is just not going to work.
- What does count is your ability to solve other people’s problems.
Another Crucial Piece of Career Strategy
Every quarter, during Synch sessions with students, I talk about the importance of developing two “Towers of Strength.”
This is SO IMPORTANT that I will develop a full YouTube/blogpost on this … a bit down the road.
Right now, just to capture the most important element – the best strategy for positioning yourself is to have TWO specialized skill areas that overlap in some significant way, and so YOU inhabit that very special, unique high-ground of expertise in TWO areas.
This immediately differentiates you from the masses.
I’d write more … but.
Instead, watch Tim Ferriss in THIS YOUTUBE.
What This Means … Pragmatically
This section is for you, if you’re currently in an AI or data science studies program, OR if you are self-studying, self-mobilizing, and prepping for a new career in AI or data science.
Let’s stay with the Portfolio idea.
It’s still a winner.
That said, let’s refine and tweak things just a bit.
Let’s Stay Project-Focused
Projects are still a good idea.
Always will be.
You’ve got to showcase your strengths, your competency – and projects are the way to do this.
THAT SAID, we need to tweak things.
More Important than Ever …
I keep talking with students about refining, and REFINING AGAIN, their all-so-important “Problem Statement.”
Your Problem Statement is your “Holy Grail.”
Your Problem Statement goes into your Abstract and your Introduction. You refer to it again during the Discussion and Conclusions sections of your work. (And yes, we are STILL writing up a full-scale report for each project, THIS is the keystone element of your Portfolio – you want a strong report for EACH DIFFERENT PROJECT. And full-on Chicago Author/Date style, please.)
But Let’s Add a Few Layers
We’re keeping the notions of “projects” and “reports.”
But we’re going to add a few things – things that are NOT a requirement if you’re in a class with me, but which I regard as SUPER-ESSENTIAL for your career positioning:
- Executive Summary – a short (e.g., 3-page) summary of your work – emphasizing the value of what you’ve done (at the management, problem-solving level).
- One or more YouTubes – we all take in information better when we can absorb it via an audio-visual presentation, rather than just reading words. Just engages more of our brain. So, guidance for you: make your YouTubes. Yes, this is a new skill level. Yes, it’s more work. Do it anyway.
- One or more YouTube #shorts – you’ve heard of the “elevator pitch,” right? Well, a YouTube #short is your elevator pitch – with visual support.
Almost no-one will read your code. Ever. (Unless they really, REALLY want to do a project themselves, and your code is their starting place – and how many people like that are there?)
And realistically, very few people will read your report. Again, people are stressed. People are more than stressed – they’re exhausted. And there is more stuff to read, and the amount of stuff keeps growing.
So – you NEED your code, and you NEED your data (if you created or curated your own data set), because these authenticate you.
But no one really has the time to check these out in detail.
You also NEED your project report, because – again – it authenticates you.
But what people will watch and read will be the EASY STUFF FIRST.
- A one-minute YouTube #short will get more attention than a full-length YouTube.
- A YouTube will be watched first – before someone reads an Executive Summary. (Especially if that YouTube is relatively short, e.g., 3-5 minutes.)
- An Executive Summary will be read WELL BEFORE someone opens up your report.
Makes sense?
And – ALWAYS – emphasize how YOUR WORK solves SOMEONE ELSE’S PROBLEM.
OK.
Go forth and conquer.
“Live free or die,” * my friend!
* “Live free or die. Death is not the worst of evils.” – attrib. to U.S. Revolutionary War General John Starck. https://en.wikipedia.org/wiki/Live_Free_or_Die
Alianna J. Maren, Ph.D.
Founder and Chief Scientist
Themesis, Inc.
Resources and References
Prior Related YouTubes
Thinking through how to learn AI fundamentals (the science behind AI):
This YouTube gives you the two most useful, step-by-step, specific job-transition guides that I’ve used – time-honored, beloved by many.
And in THIS YouTube, I discuss two books that help you shape your overall ongoing life-strategy to continuously build the elements of your ongoing success – “Atomic Habits” (by James Clear), and “The Twelve-Week Year” (by Brian P. Moran with Michael Lennington).
Prior Related Blogposts
- Maren, Alianna J. 2022. “Strategizing Your Research Project: Developing Your Portfolio Elements.” Themesis Blogpost Series (April 5, 2022). (Accessed Sept. 15, 2023; link.)
Readings
The article that kicked off this blogpost:
- Jung, Haebichan. 2019. “Sorry, Projects Don’t Get You Jobs: How we overestimate the role of Data Science projects in the job process — and the 4 interviewing skills that actually matter.” TowardsDataScience.com (Dec 1, 2019). (Members-only article.)