Hey friends,

5 years ago, I was still in college. Back then, the data science field was still pretty new (at least here in Singapore), hence it wasn't a common career path yet.

Yet I still decided to transition from physics into data science after working at CERN during my internship. Because I saw firsthand how data science could be applied in various applications and businesses beyond research and development.

5 years after, I'm glad I took the leap of faith. Data science has become increasingly important in almost every company. Interestingly speaking, it has also become a common career path nowadays.

However, mass layoffs in tech are happening around the globe due to the economic downturn. Big tech companies like Meta, Stripe, and Amazon are cutting thousands of jobs. This begs the question:

And my answer to this question is:

Here's WHY👇🏻

🤔 What is recession-proof?

Let's define the meaning of recession-proof so that we're on the same page. Here's the formal definition by Investopedia.

In our context, when we say a job is recession-proof, we don't mean that the job is immune to layoff. Instead, we mean that job is still in demand and that any person could still land a job within a reasonable period despite the recession.

Tech Winter is here, but it won't last.

Based on the global outlook, talking with investors and my friends who are running tech companies across the regions. Unfortunately, we are in one of the worst times in history for the tech industry. And yes, tech winter is here, but it won't last.

Most massive layoffs come from high-growth tech companies that have been over-hiring and seeking high growth at all costs by burning their cash along the way. Because of that, cost-cutting measures kick in and employees become the victims.

But that doesn't mean tech jobs are no longer in demand anymore.

In fact, a quick comparison between data science and software engineering on Google trends in the last 2 years shows that more people are interested (and therefore searching) in the data science field despite the current bad time.

Job opportunities are everywhere

The good news? Job opportunities are still everywhere.

As of today, there are more than 6500 jobs listed on LinkedIn hiring data scientist roles in Singapore despite the economic recession.

Wait... Why is that so?

• Aren't hiring freeze and layoffs happening to most companies in the market?

• Why are these companies still hiring?

Again, the quick answer is that hiring freeze and layoffs mostly happen to high-growth tech companies that have been over-hiring and burning their cash, hoping one day they would become profitable.

This isn't true for most SMEs in the market which represent about 90% of businesses and more than 50% of employment worldwide. While the media wants to garner more attention by showing us "mass layoffs" on their news, it's important to realise there are still plenty of job opportunities in the market, especially in the data science field.

Be irreplaceable because of your skills

No job is irreplaceable in today's market, but you can become more irreplaceable by equipping yourself with indispensable skills (technical and soft skills).

Below is the breakdown of the technical and soft skills that I believe are indispensable as a data scientist:

Technical Skills:

• Statistics

• Programming

• Data Engineering

• Cloud Computing

• Data Analytics & Visualisation

• Machine Learning & Deep Learning

Soft Skills:

• Writing

• Consulting

• Storytelling

• Public Speaking

• Domain Knowledge

• Collaborate as a Team

Conclusion

There are many companies (especially SMEs) undergoing a digital transformation which would further boost the demand for data science roles once they are ready to start collecting or leveraging data they have to solve business problems.

As more SMEs are moving toward digital transformation, more data science jobs would be created in the near future.

Therefore, in my opinion, data science job is recession-proof.

If you are looking to go into data science but wondering how you can do it, simply reply to this email and I'll try my best to answer them.

Meantime, you can also read my previous issue on how to build a solid data science portfolio to increase your chances of landing your dream data science job.

Till then, I wish you all the best and a happy new year! 😊

🚀 Whenever you’re ready, there are 4 ways I can help you:

1. Book a coaching call with me if you need help in the following:

2. Promote your brand to ~1000 subscribers in the data/tech space by sponsoring this newsletter.

3. Watch my YouTube videos where I talk about data science tips, programming, and my tech life (P.S. Don’t forget to like and subscribe 💜).

4. Follow me on LinkedIn and Twitter for more data science career insights, my mistakes and lessons learned from building a startup.

That's all for today

Thanks for reading. I hope you enjoyed today's issue. More than that, I hope it has helped you in some ways and brought you some peace of mind.

You can always write to me by simply replying to this newsletter and we can chat.

See you again next week.

- Admond