I decided to pursue a career in tech about 1.5 years ago, I start on Monday.

written by one of you guys

The main lesson from this is… If you don’t reach out to me, I can’t help you. I’m not a mind reader.

PS: I told you guys, your titanic kaggle project = 100% worthless

If you want to become a data analyst/science/MLE, you should become a paid sub, join the discord, read the material and THEN reach out to raptor with any questions.

Raptor:

• Provides direction on how to start

• Provides help with resume writing/interview prep

• Wrote industry threads re: jobs interviews I had

• Wrote questions specific to the job descriptions for 2^nd interviews

• Provided accurate, actionable information that has allowed me to change from a job in pharma to a career in tech in a little over a year for the price of ~$100

• Raptor also provided encouragement throughout the process, which is very helpful when stepping out into the unknown

I cannot recommend his Substack enough. My time is limited to 1-2 hours per day of study because of other obligations. I think that anyone who legit puts in work can get a job as a data analyst with the information he provides.

The Long Version:

I am a pharma R&D scientist and I'm switching to a career in tech with the help of a cartoon raptor. The main reason: Pharma R&D is tough to build a side biz around as the startup costs for your own lab run in the millions of dollars. Data has many opportunities; there are opportunities to freelance for small businesses, there are SaaS apps, etc.

What Raptor Did for Me

I was a free subscriber in February 2022, raptor DMed me and said he was going to do a paid option and offered me a free month. His free content is great, his paid content is BETTER so after my month was up, I bought a year's sub. 

A few months later, raptor DMed me again asking how everything was going. He helped me to get my resume together and encouraged me to start applying.  In summer of 2022 I sent out ~150 applications and had two interviews for data science positions. I bombed one interview but the second went well. During my technical interview I absolutely melted down. I forgot how to use a for loop and the split function to sort version numbers...

As a result, I spent the next month going through raptor's python articles and recommended python practice. This wasn't going to happen again.

In October I started applying again, I sent out ~200 applications over the rest of the year and had a single interview which went well. The interviewer asked if I had any samples of work and I sent (in retrospect) an awful Kaggle titanic workbook. I didn't hear back. I also noticed that I wasn't getting as much traction as the economy started to turn.

Without any traction for Data Scientist positions, I decided to change strategies. I turned my attention to Data Analyst positions. Pursuing Data Scientist over Data Analyst position was hubristic given my experience. Raptor recommends people without any experience to start with analyst positions and move on to scientist, ML engineer or data engineer positions after a year or two. Raptor again helped me to reword my resume and encouraged me polish SQL/PowerBI skills if possible. I started applying again in February, this time to Data Analyst Positions.

In April I applied for a job as a data analyst at an F500 company. Three days later I was contacted for an initial interview. I DMed Raptor and he wrote a thread about how data science could be applied to the industry. I studied SQL and general stats using the resources provided by Raptor and his substack. Raptor helped me to craft questions to ask the interviewer using the thread he wrote.  I heard nothing back for almost a month and thought it was a lost cause. I was contacted at the end of May and asked back for a second interview.

With the knowledge/notes I took during my initial interview; Raptor formulated a bunch of questions I could expect to see in my second interview. In preparation for my second interview, I used these questions, Raptor's SQL articles, Raptor's stats articles and notes I had taken while completing PowerBI training put out by Microsoft.

What I did for myself

Raptor gives great guidance but he can only point you in the right direction. As an individual, you also must put in the work. I spent 1-2 hours almost every day for more than a year working towards this; learning Python, SQL, and PowerBI, sending out applications and prepping for interviews.

Python

First, I learned Python. I ran through a bunch of exercises. That wasn't enough as shown by my inability to create simple python code during a technical interview. I ran a bunch more exercises and eventually spent a month building out a project. I built a very basic Point of Sale program that's around 1000 lines which I could point to (although I didn't) during my interviews. In this program I used most data types (strings, lists, tuples, dictionaries) as well as control flow. I read in and wrote to files and created a few classes. The one thing that I didn’t do that I wish I did was unit test. I just ran the same program over and over in pycharm until I worked out the bugs.

I learned more in the month I spent writing this than in the 6 months I spent learning python. Find a project that makes you do all these things and you will be a much better coder coming out the other end.

SQL

I ran through Raptors SQL articles. I watched all 100ish YouTube videos he recommends and completed all the exercises he lists in his articles on preparation. I knew enough to answer all questions about SQL in my interviews but I don't feel as comfortable with SQL as I do with Python. If I was still job hunting, I would build out a SQL database using some type of sports or sales data that would allow for a lot of joins and subqueries.

Applications

In the last year I sent out 453 applications (I have a spreadsheet). I heard back from 10 of them. Two companies ghosted me prior to the initial interview, leaving 8 initial interviews. I had 3 second interview. I have one offer in hand.

PowerBI

I started learning PowerBI starting in Fall of 2022. I cannot remember if Raptor wrote about it in an article or I started seeing it as a requirement in a lot of jobs. I chose PowerBI over Tableau only because the company I worked for had open licenses for PowerBI. I started trying to use BI to organize and display data generated as part of my job in pharma R&D. I replaced all uses of excel with BI in my daily work. To learn BI I would recommend completing the Microsoft training over a few weeks followed by ChatGPT and YouTube for more granular learning as needed.

What I would do Differently

Humility

Listen to Raptor. Every decision point in which I thought I knew better whether it was regarding material or applications, I did not know better.

Don’t try to go straight to data scientist unless you already have data or software experience or majored in something like computer programming. Be honest with yourself. If you are >2 SDs above the norm in intelligence and work ethic (you probably aren’t), you might be able to jump straight to a scientist position. Otherwise go for analyst and build your skills there.

Project Work

I am very comfortable with Python and BI, not so much with SQL. I think this is because how I learned them in that BI and Python, I have very real projects I can talk about and point to when asked questions. Anything you want to learn you should learn by doing because you'll have to troubleshoot problems as they arise. You can talk about the process AND function in an interview.

SQL and Analytics Software > Code

If you're going the data analyst route, learn SQL and PowerBI or Tableau to secure your analyst position. I spent more than half of my time learning and improving python skills specifically because I was aiming for a Scientist position. I will use Python in my new position, and my new manager seems very excited at the prospect of having an analyst who can code on his team BUT there was maybe 1 question on python/R during my interview and it was in the context of using python to create a visualization in PowerBI.

Apply More

It’s a number game. Every time I buckled down and sent out 50 apps in a weekend, I got at least one interview. Raptor has several articles on finding jobs via LinkedIn or Indeed using keywords beyond “data analyst.”

If you’re on the fence, go for it.

Raptor has a great substack that contains actionable information for breaking into a data role. Follow his instructions for the sake of efficiency. It will take work. But it is achievable. The blueprint laid out in his substack was invaluable to be for switching to a tech career. Had I followed the advice more closely, I might have started my analyst role 6 months ago, but here I am starting as a data analyst for an F500 company next Monday.

Thank you BowTiedRaptor, I cannot wait to see how I can apply your data alpha in my day-to-day to climb from analyst to scientist or MLE.