Hello you all! I revamped my website! Check this out: https://dataconcierge.co

This is in preparation for my book launch. I also upgraded the look of my blog. Carrd.co is amazing in combination with Drop In Blog. After struggling with WordPress.org for a long time, I gave up. Apparently, my data engineering skills are not good for web design. I learned so much about CSS.

How to Bounce Back After Rejection as Aspiring Data Scientist

Imagine this. A real computational scientist couldn’t get a job as a data scientist.

What Happened

I failed to secure a data scientist role despite my background in statistical genetics a few years ago. With 3 years of experience in consulting, I definitely spoke good enough business lingo to get by.

How could I fail at getting a job as a data scientist?

During my interview with one of the biggest pet food online stores, I kept probing what kind of business problems they’d like to solve.

“Are you concerned with the sales not doing well in certain demographics?”

“Are you worried about your ad reach and wanting to double down on where the sales are strong?”

“Do you need to classify customers so you can sell them more of what they need? For example, dog owners will get more ads about dog accessories on their Facebook page from your company’s ads.”

They couldn’t answer any of my questions.

During the tech interview, I showed that logistic regression would be great for predicting sales in certain customer populations.

“I don’t think that’s data science. We want advanced models.” The young data scientist replied after a long pause.

You wonder why data science has failed to solve core business problems and realize monetization.

Self Doubt

It’s embarrassing to admit that I actually doubted myself after this interview, thinking maybe I didn’t know science at all.

Quickly, I realized how stupid this was.

The marketers didn’t think I was good enough for data science.

That didn’t stop me from getting good jobs in data analytics.

Back to Basics

I decided to focus on the groundwork in data analytics:

Building databases and reporting dashboards with excellent customer service.

During my time in consulting, this was the most popular ask from our clients. There was a skill gap for these core needs in the field. It was as if most companies didn’t have anyone who knew how to do this. Although odd, it was good business for us.

Looking back, I believe what I’ve focused on in data analytics is truly the core of what most businesses need. It was indeed a blessing in disguise that I’ve focused on the area where the most value can be offered.

Anything else is nice to have. After a decade of the data science hype, it has yet to monetize for most companies. I wonder how many data analytics teams were ruined by pursuing of data science.

Remember, it also takes a specific kind of business to support machine learning models beyond the core functions in data analytics.

Core Functions or Data Science?

This isn’t about only making dashboards and pushing data science aside.

It’s about what stakeholders need to solve business problems.

Do most business use cases need data science? No.

Can some businesses benefit from complex machine learning models? Yes.

Are you doing stakeholder-driven data analytics?

Looking Forward

Think for your stakeholders without the strong grip of the marketers out there.

Who are they to tell you, a data professional, how you should help your stakeholders?

There will always be strong demands for basic things like data warehousing, cloud architecture, SQL, etc. This is a solid business to be in.

That doesn’t mean you should stop learning about the new things in the field. I forced myself to learn Tableau, Power BI, AWS, Azure, Python, etc. Continuous learning is a must in data analytics.

When your stakeholders need data science, you better be ready to create models.

Before you strive to learn the next new thing in the data field, think about what the shortest path is to provide value to your stakeholders.

Start with core skills and then expand.

Get to know the stakeholders and their fields of expertise.

Focus on building a relationship with them.

Stakeholder-Driven Data Analytics

Data analytics is not for the faint of heart. To be successful, you need to learn constantly and communicate like a businessperson.

However, it’s also a rewarding field, knowing that you’ve saved people hours of meaningless work in Excel, giving time back to their lives. With your help, they can truly be strategic, no longer tactical.

Let’s strive to do stakeholder-driven data analytics together.

If you're interested in talking to me directly, I'm available on Clarity.fm:

If you like me to

1) guest post on your platform,

2) provide copy writing service, and

3) help with data project management.

Feel free to book a discovery call via Calendly here.

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I'm now available for podcast guest appearances! You can find all my details and get in touch to book interviews via this link below.

https://www.matchmaker.fm/podcast-guest/mo-villagran-f84572?utm_source=social&utm_medium=referral&utm_campaign=profile

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