After working as a wildlife biologist for six years, Jackie Zuker went to graduate school for bioinformatics, but when she graduated she couldn’t find a job in her hometown of Auburn, California. She realized she needed data science skills, so she enrolled in Thinkful’s Flexible Data Science Bootcamp. Jackie tells us how she balanced caring for her young children, and part-time job, with studying, how much she appreciated her experienced mentor, and how her Thinkful project helped her land a job before she graduated as a data analyst!
What is your pre-bootcamp story? Your educational background? Your last career path?
Prior to Thinkful, I pursued a bachelor’s degree in biology. I worked as a wildlife biologist for six years, but I wanted to get into a more technical space, and work more with numbers. I thought the best way to do that would be to transition towards bioinformatics, which is large-scale data analysis centered on studying genomes, population dynamics, and things like that.
So I got my master’s degree in bioinformatics and graduated in 2016. It turned out there weren’t a lot of bioinformatics jobs in my rural area, but I did notice a lot of data science jobs. So I made the decision to work towards learning data science instead of moving to a city.
Why did you feel you needed a data science bootcamp, as well as your bioinformatics degree?
I joined this data science bootcamp because it taught the skills that I was lacking in many of the jobs I was applying for. Joining Thinkful ended up being the best decision I’ve ever made – that money was so much better spent than even the money I spent on my graduate degree. I showed some of the projects that I built through the data science bootcamp to my interviewer for my current job – those projects got me hired.
Did you try to learn on your own or break into data science before you thought about a data science bootcamp?
I’m a very good self-directed learner, but I wasn’t sure what to study, and in what order to study it. I decided that having the bootcamp curriculum would catapult me into this career much faster. I could’ve learned on my own, but if I wasn’t studying the right things, I wouldn’t get where I wanted to go.
How did you choose which bootcamp to go to? What made you choose Thinkful specifically?
I liked that Thinkful offered a Flexible Data Science Bootcamp where you could study a part-time or full-time. I had a part-time job as a wildlife biologist while I was studying, and there were some weeks where I didn’t work at all, and other weeks where I worked 40 hours a week. So having that flexibility was really nice. The fact that it was all online was a big plus because I didn’t have to commute to the city.
I also appreciated the customer service at Thinkful; the people I talked to were available to answer any questions I had. Thinkful had a scholarship for women of $100 per month, and financing options – they just made it as easy as possible for anyone to join. I was a little hesitant at first, but I started with their mandatory Data Science Prep Course, which was a good way to test out their system and see if it was something that would work for me. Also, their curriculum included SQL and machine learning which were important to me – those were skills I had been seeing on a lot of job postings.
Did you look at any other data science bootcamps?
I looked at all of the bootcamps that I could find information about. I didn’t really want to be gone from home for weeks on end so it had to be very close or be online. I also wanted to begin as soon as possible, and some of the online options had only a couple start dates that I didn’t want to have to wait for. I needed some flexibility on the meeting times as well, so that I could work or take care of my kids when I needed to. Some of the shorter also bootcamps didn’t seem like their curricula would go into enough depth for my needs. They each had various pros and cons, and in the end, Thinkful was the one for me.
You mentioned that Thinkful offered financing options. Did you use financing, and what was it like?
I did. The course is $1,500 per month, and so the loan provider pre-financed four months of curriculum for me. It was pretty easy. There was a credit check involved, pretty low payments, and then when I finished early, they actually reimbursed any unused funds.
What was the application and interview process like for you?
My application was basically the capstone project I worked on in the Python prep course I mentioned. I worked hard on it, and they were really pleased. The project was based on a Kaggle competition of predicting home prices. I used Seaborn, different Python graphing tools, Jupyter Notebook, and a certain amount of analysis using Python; which were all skills introduced in the prep course.
What was your study set up like? How many hours per week were you studying?
I have two kids under five years old, so I signed them both up for preschool. That gave me eight hours a day where I could dive into this bootcamp. I was going at it 50 to 60 hours a week because I was really passionate about the subject and I wanted to progress quickly. The format of the course broke up a lot of complex subjects into small bite-sized pieces, which made it easy and a little addictive to do “just one more lesson.” I worked during the day, on evenings, and on weekends. In total it took me about 3.5 months.
How did you balance your job as a wildlife biologist with your studies?
Whenever my company needed me I just did that instead. The whole set up with the Thinkful data science course was flexible and I was progressing fast. At the end, I started interviewing a lot and working a lot, which started to impede on my study time, but it was fine because I still was able to carve out some time here and there.
What was the online learning experience like at Thinkful? How were the days structured and how did the instructors deliver the material?
On the first day, we received the entire curriculum. It’s mostly Jupyter Notebook format, and really well-constructed reading materials, with interactive coding blocks, graphs, and pictures. There were challenges dispersed throughout the curriculum. The main component that I thought was really great was that you meet with a working data scientist mentor for three days every week for an hour. I liked my mentor a lot – it was an incredible opportunity to be able to interact with someone so experienced. Thinkful considers that time your time, so you don’t have to just talk about the curriculum, you can dive deeper into concepts beyond the curriculum, get career advice, or you can talk about anything else on your mind that day.
How did those mentor meetings fit in with your part-time work? Did you communicate outside of those meeting?
My mentor was very flexible. We had a loose framework of when we would meet, but that actually changed a few times. He was also traveling a lot, so if he had a plane ride or if I had a sick child or something, it was pretty easy to work around. I could email him anytime, or message him on Slack, or call. There was no shortage of ways to get in touch, and he was very responsive.
How often did you interact with other Thinkful data science bootcamp students?
Thinkful has Slack channels set up, so you can ask other students data science, programming, and job interview questions. Each of the mentors also sets aside a few hours a week to be available for office hours – you can pop in almost any time during the day to talk with somebody and ask them a question.
What is your favorite project that you built at Thinkful?
I continued to work on and improve the initial home prices project that I built in the prep course, and I even ended up submitting it for the Kaggle competition. I used Python, a lot of scikit-learn modules, and Jupyter Notebooks. I was pretty happy with how it turned out. I’m actually going to give a presentation on it in a few weeks to a local women in data science meetup. Thinkful encouraged me to find a local data science meetup, and I found a great one. It’s going really well so far, and now they want me to speak. I feel like, “wow this is awesome.”
How did the bootcamp prepare you for job hunting?
Thinkful provides job searching tips and advice throughout the course. We did a mock interview, where you dress up and they ask you various questions, grill you a little bit, and give you feedback immediately afterward, so that was really useful. The mentors also gave me advice about presentation skills, and really encouraged me to speak with authority and confidence about data science subjects. I ended up finding a job before I got to their official career module. I think there was another mock interview I would’ve done, but I did not end up needing that.
In the prep course they encouraged us to find meetups to attend. They said even if you’re not job-hunting yet, you want to start to get your face known, and meet some people, so that a few months down the line when you’re beginning to look for a job, you’ve already built up these relationships. So I started that early, and I’m still going to those.
Congratulations on your new job! What is the role and how did you find it?
It’s a data analyst position at a local company in the entertainment industry. I found the job on glassdoor.com. During the interview, I talked about my background, and the interviewer was most interested in my data science knowledge. I showed him my supervised machine learning project with the home prices, and another supervised machine learning project predicting whether a bank marketing campaign would be successful. The business has a treasure trove of untapped data, so my projects really inspired them to see what I could do with their data using my data analysis skills.
What have you been doing in your role in your first couple of months?
Because I’m the first employee doing data science at this company, one of my first tasks was to download Python and get systems in place. They gave me free reign to start building some algorithms. Once I had built a project, I created a presentation, and that is now moving through the systems. So I’m building projects, presenting them, and doing various kinds of data analysis on their existing departments.
They want me to analyze how to use those marketing dollars as efficiently as possible and how to direct them to the right people. So that’s one thing we’re working on right now. It’s been super interesting and fun. It’s a big change from wildlife biology for sure.
Are you using the technologies you learned at the Thinkful bootcamp, or have you had to learn stuff on the job?
SQL and Python are huge in this job, along with Excel. But actually, the Thinkful program was really spot on. I’m not able to use Jupyter Notebooks here, so I’m using a different Python environment.
How is your previous background in biology useful in your new job so far?
It hasn’t been too useful, but I was ready for a career change. I did get another job offer at a hospital as well, where I would’ve used more of my biology and bioinformatics skills. But the environment at this company was a little more enticing. The hospital was still using Excel 97, so I could see right away that it would be really hard to change or do anything new there. However, I was doing some project management in my last biologist position, so that’s always useful, being able to delegate tasks, use time efficiently, and things like that.
What’s been the biggest challenge or roadblock in your journey to becoming a data scientist?
So far things have been pretty good. I wondered if gender would be an issue, but so far it really hasn’t been. It seems like business people will see these data science techniques and get pretty excited. Data science is so new and so useful, and people can really see the value in it right away. These skills have opened so many doors.
How do you stay involved with Thinkful? Have you kept in touch with other alumni?
Just a little bit. I’m still on the Slack channel, so I’ll pop in there, and interact. I haven’t talked to my mentor too much recently, but he’s busy traveling the world. Hopefully, we’ll talk again at some point – that would be fun.
What advice do you have for people thinking about going through an online data science bootcamp?
It’s extremely hard and also extremely rewarding. If you have the motivation to learn new techniques, continually update those techniques as the field changes, and if you like to be constantly learning – then data science could be a really great profession for you.