5 Essential Lessons for Junior Data Scientists I learned at Spotify (Part 1)

The First-Years Chronicles of a Data Scientist in Tech

The insider’s guide to crushing your first years as a data scientist in Tech and levelling up your game.

Congratulations and welcome to the adventure! You’re a Data Scientist in the making and your journey is only getting started!

You’ve graduated from college and now you’re diving into a world of accomplished people who are changing the game. Sure, you may not be one of them (yet!), but you’ve just embarked in a journey to become one. You’re learning and growing every day as you discover the role that lays ahead of you and what it takes to excel in it.

But wait, weeks or months go by and the reality is; you’re still a student in your head. You probably don’t even know it, because the switch didn’t flip just yet.

If there is one thing I learned when starting my career in tech, it’s this :

College gave me a good technical head start, but some things are just being taught on different school grounds.

So, if you want to save yourself the sweat from finding out what core skills you may need to navigate your way as a starting data scientist, then you’re definitely at the right place. As a matter of fact, I hope any fresh graduate from any industry can find advice here!

Here, I am not only sharing with you my learnings, but I am also providing you with useful tips to help you avoid having to mess up in the first place. So I really do encourage you to keep on reading!

But first, let me tell you a quick story!

For years, Spotify had been the ultimate workplace for me. I knew I’d thrive there as it exactly combined everything I wanted in a career :

People with similar interestsA balanced work-lifeAn innovative environment to learn and growAnd most of all, as a violinist myself, I highly valued working in a place where music was a core element

After some good amount of hard work, persistence aaaand a pinch of luck, I managed to finally make my way into the wonderful land of Spotify

Photo by Razvan Chisu on Unsplash

Fast forward, 2 internships, a master thesis and a full time offer later, I had finally landed the job of my dreams and man, was I thrilled.

At this point, I had spent a good amount of time messing up enough through projects that I ended up learning some pretty valuable lessons. Lessons I just wish I had learned sooner, as it would have saved me considerable time, and spared me the frustration of repeatedly hitting my head against a wall when the door was right beside it.

The right way to doing things the wrong way

So there you are, you do valuable work, pick out some cool insights, and maaybe you even manage to throw in there some good recommendations! Proud of you; you can give yourself a high five!

But if you’re like me, it took you weeks or months to share the fruits of your labor with key stakeholders. People are only just coming across your work for the first time. Why? Because you just went MIA through most of it.

One key mistake I made along the way was to carry the student mindset with me.

Photo by Siora Photography on Unsplash

I would drown forever in a bubble every time I would take on a big project. You might tell me; ‘K (that’s me 👋🏼), okay you made the mistake once but three times? Come on, were you sleeping when the lesson was slapping you in the face?’ … Actually, I was wide awake, but it did take some time for it to properly kick in (or maybe I was half asleep).

Data Scientists often work solo
Of course, they collaborate with a team of cross-functional people. But the data part is mostly done by one person — you. So it’s soo easy to slip into this trap when you’ve spent your college years working alone on projects and assignments. In the real world, you just can’t afford to isolate yourself.

The problem with this approach is that your work might be of great value, but if it fails to get over to the right people on time, its value might have less of an impact. People may have already started making decisions.

So if you want to make sure all your hard work gets the proper hit it deserves, you need to ditch the school act ASAP. How? 2 words for you:

Communication✨ & ✨Feedback

Lesson 1 — Continuous Communication is Key

My friend, if there is one important skill you quickly need to pick up on in the start of your journey, it is to:

Communicate, communicate, communicaaaaate!!!

I’ll repeat it as much as it needs for it to sink into your brain. Communicate your work as often as need be! The pace can be fast in tech, so if you want to make sure all your future impact does not go for naught, then communication is your friend.

How can you do that?

1. Update your stakeholders regularly on your progress, even if you’re not finished yet.

One effective way you can do this is by: Sharing some data nuggets (the most interesting pieces of insights) with the relevant people.

You can do that via:
a) Messages (Slack, Teams, Hangout, Emails…)
b) Weekly share-outs
c) 1:1 meetings (just make sure to prepare beforehand)

Whenever you stumble on a noteworthy insight, press that send button. Doing this can:

Help you pinpoint holes in your storylineIdentify data inconsistenciesSort out misunderstandings you might have on some key concepts
and the list goes on.2. Make sure to find the right sharing cadence

Of course, the goal is not to share every day what you’ve just discovered, as sharing unreliable insights could negatively bias decisioning.
Instead, you rather want to:

Iterate over different sharing frequencies until you find the right oneMake sure to hold on a big banner screaming “Work in Progress” 🚧

In school, we can go on weeks working hard in our bubble. Projects may get shared out only after a long period of time and only when they’re done. In tech, no one got time for that. So pick up the pace as soon as you can💨.

Lesson 2 — Ask for Feedback from the Relevant Stakeholders

GIF by Author

Press hard on that feedback loop. Actually, you want to hug that feedback loop. You’ve just made a new friend. Congrats!

Seeking feedback regularly on your progress from your manager or whomever more experienced is working close to you is crucial. The key here is to also learn when to ask for feedback. Remember, finding the right balance applies to everything.

This will save you from spending a long time building up the wrong narrative, only to end up having to change it again. So better get your storyline straight as early as you can.

Asking for feedback and communicating your insights are two sides of the same coin.Communication enables you to keep your stakeholders up-to-date with the content of your workFeedback allows you to double-check that you’re delivering the right content of work

How can you do that?

1. Share your doubts, thoughts and findings by tagging the relevant people on your working documents or decks.

Something I learned at Spotify is to seek feedback from the right people by tagging their name, on documents or slides, on the parts where I need to have their opinion on. Of course, don’t forget to follow up with these people via messaging if they ever miss your cry for help.

2. Schedule regular meetings to discuss your work and any roadblocks you encounter

Here’s one tip :

Book 1:1 meetings with the most relevant stakeholder(s) to directly discuss your doubts, thoughts and findings.Make sure to outline in a document the context of your work + only the things you need feedback on. This way, you’ll only address the most important elements and avoid wasting time for everyone.

Senior-level people are wizards, and you want to be sprinkled by that magic dust 🪄. If you’re as lucky as I am to have an amazing manager holding your hand to help you grow, then be sure to make use of it. Your coworkers have that domain expertise that you’re still working on to acquire, so they see things with different eyes.

They will definitely aid you in :

Picking up plot holesRefining your storylineGive you more contextTeach you new skills as they see you running in circlesBig picture thinking is paramount when you’re a data scientist

But you’re still a puppy and your eyes haven’t fully opened yet. So you do need another pair of lenses to shed light onto the dark spots.

A snapshot of me on my first year in Tech (Photo by Isabela Kronemberger on Unsplash)

Communicating your insights and regularly seeking feedback not only helps you keep your project on track, but it also enables you to build trust with your team and stakeholders. When they see your work and know what you’re doing, they’ll be more likely to support you and your ideas.

Enough for now.

This article is the first of a two-part series in the “The First-Years Chronicles of a Data Scientist”. Up Next: Part 2

In subsequent parts of this article, I’ll elaborate on the other lessons that I learned in my first years at Spotify that can fast track you to succeed in your Data Science journey!

If you’ve enjoyed this article or found it useful, then please follow me for more stories on my journey, or leave a clap so other people will see this here on Medium. And if you just know someone who might find this relevant, then please do share it!

5 Essential Lessons for Junior Data Scientists I learned at Spotify (Part 1) was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.


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