K#11. How to handle work pressure effectively
Insider tips from Expert Data Scientists to thrive in high-pressure tech roles
Hey there 👋
Welcome back to K's DataLadder ✨! Each week, I share a story from my life as a Tech Data Scientist to help you level up in your career (and sometimes in life too).
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This week, we’re diving into something we all deal with but rarely discuss: stress at work, and how to manage it. Given the current job landscape and the pressure to perform, it's crucial we talk about this.
As you grow in your data science career, you'll find that improving isn't just about technical skills. It's more about managing stakeholders, organizing your work, and handling stress. These 'soft skills' become just as important as your technical abilities for your success and well-being.
Reading Time: 6 minutes
Agenda
Life checkpoint
This week’s story
Advice from Experienced Data Scientists
Life Checkpoint: Keeping it real 🌿
Remember when I said last week that I wanted to chat with some of you on a call? Well, it happened!
It was awesome to hear about your experiences and figure out how I can make this newsletter even more helpful. I also realized that some of you aren't quite sure what my newsletter is all about.
So let me clear that up: I'm here to show you what being a Data Scientist in Tech is really like. Everyone's curious about it, but no one truly knows until they get inside.
If you’ve missed the opportunity to meet, don't worry! I'm planning to do this again soon. So keep an eye out on future issues – you might just snag a free 30-minute 1:1 session with me (usually worth $100, but for you? Absolutely free 🎁)
And before I forget – if you got any topics you want me to cover? Questions bugging you? Drop them in the comments. Your burning questions could be next week's topic!
This Week’s Story
The past two weeks have been... intense, to say the least.
I've been drowning in A/B tests, my screen blowing up with notifications from a million different Slack channels, group chats, and threads.
But A/B Testing is THE skill I’ve been wanting to master the most so I made sure I had lots of projects assigned to me to practice on.
But to top it all off, I’ve also had this huge deep dive analysis that was due… last month 🥲.
Because of all that, the stress started piling up fast.
School doesn’t really teach us how to manage this kind of workload, the constant context switching between tasks, and the underlying threat of layoffs in this economy.
It’s not my strong suit at all.
I’ve mentioned my ADHD before, and it’s like a double-edged sword. On one end, I can hyper-focus for hours on one task (if I’m interested). On the other end, actually getting things done? Puts my brain into overdrive.
So last Wednesday, I thought I'd use our "Focus Wednesday" (our weekly meeting-free day at Spotify) to finally tackle this deep dive. But as soon as I started looking at the project scope, I felt my heart rate fly through the roof.
How in the world was I supposed to get this done? Where to even begin? What to prioritize? I had a panic attack.
Plot twist – It's not just me feeling this way.
I shared my struggles with one of my Spotify friends who’s the best Data Scientist I know and he told me he was working on a massive deep dive that left him as overwhelmed.
It was weirdly comforting to know that even the pros sometimes feel out of their depth.
The next day, during our Data Science forum - a meeting where we chat about our ongoing challenges, like a group therapy session, I told everyone about my struggles to keep up with all the requests and set boundaries.
It was the best thing I could've done.
My team - these amazing, experienced Data Scientists - just got it. They started sharing their own war stories and giving me valuable advice. It hit me then how lucky I am to work with smart and caring people who always have my back.
I know not everyone has a dream team like this, so I wanted to share some of this wisdom with you guys. We're all in this together, after all.
Advice from Expert Data Scientists 💎
These could help you manage stress and stay on top of things in our fast-paced data science world.
We’re expected to complete projects, answer messages, keep up with announcements, attend meetings, and somehow maintain a life outside of work.
It’s a lot.
I’ve started implementing some of these strategies, and I’m already seeing a difference!
#1. Organize your Slack 📚
(Or whatever messaging system your company uses, Teams maybe?)
My friend Adri, who's an excellent Data Scientist, suggested creating priority groups in Slack: P0, P1, and so on.
P0 is for the most important channels that need your immediate attention.
This helps you catch the most crucial information at all times despite all the noise in your notifications.Last week, I missed some specific guidelines for my A/B tests that were posted in one of the channels a while ago. I panicked at first then I felt embarrassed explaining to my colleagues that I sometimes miss important messages because it's hard to keep up with everything.
But they said I shouldn't feel bad about this. No one expects us to track every single message. We just need to focus on the most critical stuff.
That's why grouping your channels can really help. I've already done this in my own Slack, and it's making a big difference.
#2. Day-Box your Time 🗓️
One of my colleagues mentioned that our Design Leader blocks specific times in her calendar for different tasks. This includes not just work tasks, but also time for checking messages, replying to emails, and updating the roadmap.
I’ve never been good at time-boxing my days so now I'm trying something different: day-boxing my time.
I'm setting aside certain days or half days of my week for specific tasks.
Some days are for A/B tests, others for deep dives, and I even have specific times for checking messages.This helps me avoid constantly switching between different types of work. I've realized that reading and replying to messages at random times really disrupts my focus.
It takes a lot of energy to refocus on a task after an interruption.
My manager also gave me a great tip: it's okay to cancel meetings when I'm behind on work. She does this herself, so I'm thinking about doing it more often too.
#3. Communicate with Stakeholders 🗣️
I never thought about telling people my work preferences, but it seems that's normal here at Spotify.
I've learned it's helpful and even advised to talk with key stakeholders about how you prefer to work.I'm planning to spend some time building relationships with important stakeholders (as you can see below 👇). I want to tell them about all the different projects I'm working on, including ones they might not know about.
My data science colleagues also suggested to tell stakeholders how I prefer to communicate. For example, I'd rather get direct messages or summary emails instead of being tagged in lots of group discussions.
This way, they can be more considerate of my time and only ask for my help when it's really necessary.
Communication goes beyond sharing just about your work, it also includes sharing about your work conditions and preferences too. Everybody functions differently, and it's okay to let people know what works best for you.
#4. Set Boundaries 🛑
Setting boundaries is tough but important. I find it hard to say no because I often want to show I can handle everything, but I’ve realized it’s not worth it.
After Spotify went through 3 big rounds of layoffs, I started putting even more pressure on myself to perform well. I created this pressure all on my own. So I shared that concern with my manager, and turns out the pressure has no reason to be there.
Try to build a good relationship with your manager based on trust & openness.
When you're honest about your work and challenges, they can better understand and support you.
This way, when things get tough, your manager can help find solutions or just be there to listen. They're there to help you succeed, not just to oversee your work.My colleagues also suggested I start saying no to unplanned requests from stakeholders. They said if something isn't on the roadmap, it's not a priority.
They advised asking people to create official request tickets or to talk to my manager about new tasks if they're really important.
If people don't want to do this, it might mean the task isn't that urgent and probably isn't worth your time. It's okay to explain that you have limited bandwidth - it's fine to push back.
These strategies might not all work for everyone, but some of them probably will. Give them a try and see what helps you. The goal is to lower your stress and work better, not to make your day more complicated.
Also, feel free to share in the comments or by email some other strategies you have to deal with stress at work. After all, we’re in this together 😉
Also, if you haven’t done it yet:
My previous editions:
Please leave a ❤️ or a comment to let me know that you read me, it would mean the world. Until then, see you next week for more data stories 🫶
I'm starting to feel that pressure you're talking about when the performance of the model in production is not as good as it was with historical data, and then everybody's sending messages on Slack to know when the model's going to be fixed 🫠. Thank you for the tips Khouloud :)
It’s the screenshots for me ✨ they made the ideas clearer!