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Hey there 👋🏼 - Ali here

Welcome to the 4th edition of Career Science

👋🏼 to all the data job seekers who are curious to learn the science behind landing their dream data role.

This Wonky Wednesday (somehow I always end up with a good W adjective) we’ll be discussing ❌ 5 mistakes to avoid to network like a pro (& avoid getting 100s of unanswered DMs).

Hold on to your SQL tutorials cause this one is a 3-minute read. Read this and ignore those job postings that require cover letters. The only time I am every submitting a cover letter is for a job as an astronaut.

Ready for the search science? Well then, let’s dive in.

Just read that somebody turned down a job offer given to them on the same day. The reason will shock you. Honestly, I’d be all over that job offer. People are weird.

🏗️ Building Career Science: I took a break last week from writing my newsletter so I am excited to be back this week. I am also building a high-performance notion template to make you a 10x productive data job seeker.

🥾 Weekend Pic (end of the 📧): My hiking trip

🤏🏽 Job Search Nano-tip: Asses your job search progress after every week. Don’t overthink every decision every day. It’s a quick ticket to burn out.

🔥 Favorite Tweet: By Naval

🎯 Ali’s Aces (end of the 📧): This week we have:

Sometimes, you need to break down the problem into smaller steps to make it easier to solve. In databases, a similar idea applies when working with complex queries. You can use tools called Common Table Expressions (CTEs) and subqueries to break down a big problem into smaller, manageable pieces.

Subqueries: A subquery is like a mini-puzzle within a bigger puzzle. It's a way to use one query (the small puzzle) inside another query (the big puzzle). You use subqueries when you want to get information from one table based on information from another table.

Let's say you have a school database with two tables: "Students" and "Grades".

Students Table:

Grades Table:

You want to find all the students who got an "A" in Math. Here's where a subquery can help:

In this example, the inner query (SELECT StudentID FROM Grades WHERE Subject = 'Math' AND Grade = 'A') finds all the StudentIDs who got an "A" in Math. The outer query then uses this list of StudentIDs to retrieve their names from the "Students" table.

Running the given query would result in an output like this:

CTEs (Common Table Expressions): A CTE is like a helper table that you create temporarily to make your query easier to understand. It's especially useful when you need to repeat a certain piece of logic multiple times in your main query.

Imagine you're running a bookstore, and you want to find all the books that have been sold more than average.

Books Table:

You can use a CTE to calculate the average number of book sales first, and then use that in the main query:

The CTE named "AverageSales" calculates the average sales across all books. Then, the main query uses this average value to find books that have been sold more than the average.

In simpler words, a CTE helps you set up a smaller, easy-to-understand table (like a helper) that you can refer to later in your main query.

Running the given query would result in an output like this:

This is because the query first calculates the average sales across all books (assuming it's calculated as (120 + 90 + 150 + 200 + 80) / 5 = 128) and then selects the titles of books where the sales are greater than this calculated average (i.e., sales greater than 128). So, "Book 3," and "Book 4" have sales higher than the calculated average and are included in the output.

So, whether it's using subqueries to fetch specific data or using CTEs to make your query steps clearer, both techniques help you break down complex database problems just like solving puzzles piece by piece.

Networking is no mystery.

It’s a skill you can learn.

Here are 5 mistakes to avoid to network like a pro (& avoid getting 100s of unanswered DMs)

Sending 100s of connection requests in the hopes that somebody will respond is a bad idea.

Even if someone does respond the conversation never goes beyond “Thanks for connecting”.

And you never hear from the person ever again.

Instead, do this:

If you are networking with everyone you are networking with no one.

“Can you look at my resume”

”Can you help me make a portfolio”

“Can you mentor me? I need guidance”

None of these will get you responses.

Nobody has time for a stranger.

Instead, do this:

Don’t expect to withdraw $$ from an account you have invested $0 in.

Messaging someone to mentor you?

They’ll get overwhelmed and won’t respond.

It’s because it's a huge time commitment to mentor someone.

Instead, do this:

A: Should I subscribe to DataCamp

B: Should I pursue a Google Certificate

Since it’s a super low-commitment task.

They are more likely to respond.

Bonus: Follow up & tell them about the results of the advice.

Big asks get you ignored while small asks get you in.

On average 80% of people ignore emails 4 times before they respond.

Just following up increases your response rates significantly

But never following up gets you nowhere.

Instead, do this:

"I know how valuable your time is. Apologies, if you're not the right person to assist, could you steer me in the right person’s direction?

This works because of the Dunning-Kruger effect.

When people get their egos bruised they tend to react emotionally.

“How dare he think I am not the right person??” I’ll show him.

Follow up, stroke their ego & see the responses roll in.

Getting overwhelmed is easy when networking.

Who to reach out to?

What did we last talk about?

Did he/she respond to my message?

How long has it been since I last contacted them?

People quit when they are overwhelmed.

Instead, do this:

Create a 2nd brain & give the 1st one some rest will ya?

Networking fails miserably when you are vague about your 3 Ws:

→ What - connect on a shared experience or goal

→ Who - connect with who you can relate to

→ Why - connect with purpose

What - connect on a shared experience or goal

🔴 “Can you get me a job?”

🟢 "Hey [name], I saw your data visualization project and I am super impressed. I am working on something similar. If you are open to connecting then I’d love to show you and get your feedback on how I can make mine better. No worries if swamped with work"

Who - connect with who you can relate to:

🔴 Stop sending out 100s of random connection requests

🟢 Start sending out 100s of targeted ones with people whom you have common ground with (boot camp, education, work experience, etc.)

Why - connect with purpose

🔴 “Hi, Ali”

🟢 Have a strong call to action (CTA)

“I imagine making the transition from sales to data analytics wasn’t easy. I would love to learn more about your journey and the obstacles you had to overcome. Do you have a few minutes to chat about it? No worries. if busy. I can understand" (give a soft exit)

Go from ‘Me Mindset’ → To ‘We Mindset’

Thanks for reading!

Whenever you are ready, here are 2 ways for us to work together:

💼 Job Boards: A job board for data jobs

🤖 AI Tool: Have the perfect memory with AI

📚 AI Job Search Playbook: 50+ AI Tools & MORE

📊 Dataset for Practice: Dataset on extreme weather deaths

✅ Recruiter’s Advice: “Don’t focus on being the most qualified”

🛠️ Job Search Tool: Create portfolio presentations that get noticed

Reached the finish line? Awesome. I’d love to know what you thought of the 3rd edition of Career Science? Reply to this email. I respond to every email!