How I decided to become a Data Scientist
If you are looking for Data Science job hunting advice, interview tips, or guidance for ML techniques, I’m sorry, this article is not for you. Why? Because I’m not a data scientist yet.
But, I’m a writer, and sometimes (most of the time) people write about things they don’t yet know about.
3 weeks ago, I decided that I would become a data scientist.
Many people share their experience only after they’ve achieved their goals. I used to do that.
I would study hard, day and night, just to finally tell my friends in Vietnam that I got a scholarship to study in Japan.
I would get up at 5am, go to a coffee shop near my office in Tokyo to study for 1 hour, then go to the library at 8pm after work to study until the library kicked me out. I would do that just to make a surprise announcement to my friends and co-workers in Japan that I got accepted to an MBA program in San Francisco, and that I was moving here.
But, this time, I’m going to document my data science journey and share as it goes. Because:
1. I feel insecure trying to achieve this goal by myself (I’ll explain why)
2. People get lonely as they age (?!) and I feel the need to be in a community!
3. I want to share with you any insights that I get from talking to data scientists and people in the field. (I’m lucky to be in San Francisco, surrounded by tech enthusiasts, but not everyone has that opportunity).
So, here are my first 3 weeks trying to become a data scientist. Read on to know how I made this decision.
Week 1: sweat and tears (Career Exploration)
Just kidding, it wasn’t that bad.
I did cry a lot on the day I knew I was let go from my current job. I cried some more every day that week. I know many people lost their jobs during the pandemic. I just couldn’t believe I was one of them, especially when the pandemic was mostly gone in the US (finger crossed!). My manager brought me in 2 years ago, fought for my H1B sponsorship and patiently waited for the approval when it was delayed during COVID. So I thought, there’s no way he’s gonna let me go. Everyone in the company loved me. I was doing a good job at my current role… Everything was just like when I was working in Japan.
Well, except that it’s not Japan. And, like in a relationship, when your partner can’t afford to take you to a sushi restaurant anymore (given that eating at a sushi restaurant is the requirement for your relationship), they have to break up with you. I blame COVID for this situation.
Anyway, like it or not, I had to look for a new relationship. Luckily, so many people reached out to help in my career exploration process. First day of the ‘funemployment’, I talked to my former CMO and followed his advice of pursuing the Marketing Analyst path, since I have the data analytics background and I love working with data. Three days later, I talked to my friend at Amazon and she suggested a Product Manager career. Four days after that, I got stressed out by the fact that ‘I have no income’, and thought maybe I should stick to my current title (Product Marketing Manager) because it seems to be the safest choice…
In the exploration process, especially when you’re trying to switch career, it’s always like a roller coaster. Sometimes you lose confidence and decide to stay within your safety zone (aka. stick to the job that you know you could do). But what about getting out of your safety zone, and do what you really enjoy?
After reading so many job descriptions on LinkedIn, I started to notice my emotions. I could feel the excitement when I read a JD that lists the tasks and responsibilities I enjoy. I could feel my heart sink a little bit when I read about things I enjoy less. By listening to my emotions, I realized that I needed to follow my passion: data-driven decision making.
I decided that Product Marketing is not for me. I canceled a phone call with Lyft for a PMM role. I took a risky path. I want to be a data scientist.
Week 2: self-doubt (Research & Strategize)
Wanting to do something is one thing. Being able to do it is another story.
I don’t have a PhD. I don’t have a computer science degree. I don’t have a programming background. My career has mostly been in business. Can someone in business become a data scientist?
Being a practical thinker, I’ve never done anything without assessing its success rate. I need to know: with my background, skills, and experience, how feasible it is for me to become a data scientist.
For this ‘research’ project, I used 2 types of market research method:
- Interviews
- Social Media listening (reading)
Interviews
First thing I did was to connect with other data scientists on LinkedIn. I sent out about 20 requests. The results so far: 5 people responded, 3 people gave me some advice and encouragement, and 1 person agreed to have a phone call.
I also contacted friends and former bosses who might be able to introduce me to a data scientist, and luckily got in contact with Scott Czepiel, former DS at Airbnb. (You can read his working_with_data blogs here). Scott gave me so much advise, detailed explanation about the Analytics field, and encouragement, which I share in another blog.
Talking to people is the number one thing I recommend when you’re trying to figure out your career direction.
What I learned from interviewing other data scientists:
- Data Science is a broad field. Pick a path you (think you will) enjoy the most and develop your expertise from there.
- Most of the time, technical skills are actually not as important (and not as difficult) as other soft skills, such as the business mindset and the ability to present your insights.
- To tackle technical interviews: practice, practice, practice.
- Data wrangling takes time. If you don’t enjoy spending a lot of time cleaning and organizing the data, maybe you should reconsider becoming a DS.
Social Media
Next, I went on Twitter, YouTube, Google and started to follow people in Data Science. I read blogs, watch videos, joined Slack communities, attended webinars, listened to Podcasts and even downloaded Clubhouse…
Of course, there are a lot of noises out there. There will be articles like this which make you feel like you’ll never be good enough to be a DS because the market is so competitive.
But, think of it as a business strategy: do you invest a lot of money to compete with the market leaders, or do you find a niche for your product/idea?
I’m still developing my positioning, but I believe that with my background in data analytics, my passion in data-driven decision making, and my business mind (plus experience in Marketing, Product, BizOps…), I will be able to find my niche and be a good data scientist.
My takeaways from this Social Media reading process are:
- Know your positioning.
- Do data science projects!
- Surround yourself with a data science environment ← This method has worked well for me in the past when I tried to learn something new. The right environment (physical or digital) will remind you to learn.
At the end of week 2, I’m committed to become a data scientist.
Week 3: enlightenment
Some people don’t like routines, but I think healthy routines will help you overcome unstable time in your life. When you’re facing uncertainties, routines help you feel grounded.
At week 3, I’ve established my daily ‘funemployment’ routines:
- Do 30-minute pilates in the morning (Highly recommended! You can replace with yoga or other types of workout)
- Go for a walk in the neighborhood
- Spend 1 hour for job hunting (sending applications, asking for referrals, updating resume…)
- Learn Data Science and do Data Science projects
- Meditate for 5 minutes at noon
- Practice SQL
- Write
Sometimes I don’t have time to do all of these things because I have to prepare for interviews, but I know becoming a data scientist is my priority. And if you know your priority, you will always have time for it.
Thank you for reading and for supporting my DS journey. This article is also published on my blog (https://thuytran.io/) where I share more about myself and my projects. Connect with me on LinkedIn if you want to chat.
