How Recent College Grad Megan Pivoted into Data Science With Thinkful

Megan Dibble earned a college education in industrial engineering, but wasn’t inspired by that career path. Wanting to work on more data-driven projects, she researched bootcamps that were less expensive than going back to college for a master’s degree. Megan explains why she chose to enroll in Thinkful’s Data Science Flex bootcamp instead of a full-time bootcamp, how she landed her first data role before even graduating from Thinkful, and her tips for working remotely as a data professional. Plus, Thinkful now offers deferred tuition for Flex students, so Flex students only pay once they're hired!

What inspired you to enroll in a data science bootcamp soon after college?

I received a degree in industrial engineering from California Polytechnic State University in San Luis Obispo. During college, I held two internships where I worked to improve processes at manufacturing companies, but after those internships, I started second guessing my career choice. I was hired as a technical consultant, setting up and implementing ERP systems, but the position wasn't as technical as I wanted it to be and didn’t focus on working with data. I knew some Python, and I decided that a data science bootcamp would help me to further my coding skills plus give me a chance to apply to more data science jobs. 

Why did you choose to enroll in Thinkful’s Data Science Flex bootcamp?

When I was considering Thinkful, I was debating between enrolling in Data Science Immersion or Data Science Flex. I initially chose Thinkful’s Data Science Flex bootcamp because I wasn't sure if I was going to balance the bootcamp with a part-time job. I also chose Flex because I knew that I had the self-discipline to self-teach and pace myself properly. The Flex program was helpful because it allowed me to schedule learning in my own time. 

The Flex program was also more affordable for me and followed the same curriculum as the Immersion bootcamp. As a woman, I also received a tuition discount!

I also loved that the Thinkful bootcamps come with one-on-one mentorship. My data science mentor has a Ph.D. and is super helpful. They have been able to answer all of my questions. 

How did you prepare for Thinkful?

Before the first day of the data science bootcamp, Thinkful had me complete a few weeks of introduction work. The prework covered the basics of statistics and Python. After it was complete, I had to pass an admissions assessment test in order to enroll in the bootcamp. Since I had finished the prework and had an engineering background, the assessment wasn't hard for me. If I failed the assessment, Thinkful would have let me try again. 

What was a typical day like in Thinkful’s Data Science Flex bootcamp? 

I tried to work on the course materials for at least four hours every day. When there was a large project to complete, I would dedicate more time to complete it. The Flex program allowed me to take random days off when I needed them. Before the COVID-19 lockdown, I also went to coffee shops in order to motivate myself to complete coursework. 

Since this is a self-paced course, did the teaching style match your learning style?

There are no lectures in the Flex bootcamp. Instead there are written lessons to read and exercises to complete. Thinkful offers study sessions for those needing extra support where you can request help with specific parts of the curriculum. The only live portion of the Flex course are the one-hour mentor sessions that I had twice per week. 

What did you learn in the Data Science Flex bootcamp curriculum? 

The curriculum begins with basic statistics, math, and database concepts like SQL. The bootcamp spends an extensive amount of time on exploratory data analysis and went into depth about machine learning projects. We covered linear models and nonlinear models. 

Overall, the curriculum was extremely comprehensive, but it cannot go into depth about everything. For example, I supplemented my learning with outside research for the big data portion of the curriculum. When I wanted more information on a subject, my Thinkful mentor offered me more resources and books to include in my studies. 

Since you did this bootcamp remotely, how did you connect with others in the bootcamp?

Thinkful has a Slack channel for questions, which they would quickly respond to. I also connected with other data science bootcamp students over Zoom, which helped me feel connected as a community. These Zoom sessions were also helpful because we practiced interview questions with one another.

What kinds of projects did you build at Thinkful?

There was a capstone project at the end of every section, so by the end of the bootcamp, we had completed four capstone projects. We also had additional large assignments that I added to my GitHub repository. For one project, I did exploratory data analysis in AB testing, supervised machine learning, and unsupervised machine learning. The unsupervised machine learning project was memorable, and I'm proud of it. I took unlabeled credit card data and figured out customer segments and visuals with clustering models. We presented our capstone projects to our mentor who would then give us feedback.

How did Thinkful prepare you for your job hunt?

Thinkful sprinkles career service modules throughout the curriculum, and the end of the bootcamp especially focuses more on career prep. There were modules about saving projects on GitHub, resume work, and interview prep. Right after you graduate, Thinkful pairs you with a career coach.

Which data science roles did you feel qualified to apply for after graduating from Thinkful?

Even though I was enrolled in the data science bootcamp, I applied for data analyst positions. I found that in many cases, the data scientist employment opportunities required years of experience or an internship within that specific company. I still applied for a few data scientist positions, but data positions requiring data analytics and visualization were my focus. 

It also helps if you can leverage your degree and/or previous career. I have a friend who worked in the biomedical field and then did a data science bootcamp. After the bootcamp, he became a data scientist at a national lab because he was able to leverage his knowledge of biology and statistics.

Congrats on your first data role as a Global Solutions Analyst at Stanley Black & Decker! How did you land the job?

I landed my job at Stanley Black & Decker before I even finished the Thinkful bootcamp! While I was in the bootcamp, I blogged about my data science career journey on Medium. A manager at  Stanley Black & Decker read my blog and was impressed by how I explained machine learning models to beginners. They contacted me to set up an interview for a position they hadn't yet advertised for on their Enterprise Data and Digital Insight team. Since Stanley Black & Decker is a manufacturing company, they liked that I had a background in industrial engineering. I had two interviews and was offered the job.

What kinds of projects are you working on at Stanley Black & Decker?

The Enterprise Data and Digital Insight team is a cross between finance and analytics. I work under an umbrella team called Performance Resiliency. My team consults for the entire company, working on projects to help improve efficiencies and cut costs. We assist other teams to automate their data processing needs, create PowerBI dashboards, and provide them with a way to automate their analytics.

Are you using all the data science concepts and tools that you learned at Thinkful?

Once I joined Stanley Black & Decker, I had to learn Alteryx which is an ETL software that does analytics and modeling. Learning something totally new on the job was unavoidable, but what I learned at Thinkful, like SQL, Python, general database concepts, and being familiar with the data mindset has really come in handy.

What advice do you have for others who are beginning to work remotely in data science?

When I first started working remotely at Stanley Black & Decker, I would type out these really long emails to my teammates so I was as exact as possible about a problem. Now I know that it’s better to be short and concise with your communication. If there’s a complex issue and you're confused, it's better to hop on Zoom instead of sending a million emails back and forth with your teammates. To prepare yourself for your projects, first find out the requirements of the project.

Be aware of your computer’s limitations because the data you’re working with may be difficult or impossible for your computer to store. Find out your company’s IT rules before you store data on an external hard drive.

Is there anything you wish you had known before enrolling at Thinkful?

Since Thinkful does not have a lecture-based curriculum, be prepared for lots of reading. Recognize that every module in the curriculum will not teach you everything you need to learn about that subject. You need to research and supplement the curriculum with your own resources. I found it invaluable to have a group of other bootcamp students to help keep myself accountable and do mock interviews with. Make sure to connect with others in data science while you’re in the bootcamp.

Do you recommend other recent college grads enroll in a bootcamp like Thinkful? 

I think it depends on the person, but keep in mind that it’s more cost effective to enroll in a bootcamp than going back to college for a master's degree. If you are already working in tech, it's popular to climb the career ladder by doing a bootcamp because employers are looking for skills, not necessarily a degree. 

What has been your biggest challenge in this journey to becoming a data scientist?

My biggest challenge has been gaining the breadth of knowledge needed to be a data scientist. It’s a lot of knowledge for a beginner to learn, and trying to learn all of that in a short span of time was extremely challenging. This is why I pivoted and accepted a data analyst position out of bootcamp, because data analysis is not that different from data science and requires less knowledge to gain an entry-level position. I’m frustrated that I wasn’t able to become a data scientist right away, but the skills I'm learning as a data analyst will help me eventually achieve my goal and become a data scientist.

Looking back on your remote bootcamp experience, was Thinkful worth it for you? 

Yes, because I learned so much from Thinkful and now I have the confidence I needed to interview for data roles. I already had a statistics background from my college education, but Thinkful gave me the push I needed to start a career that was best for me. I'm happier in my new job as a data analyst!

Find out more and read Thinkful reviews on Course Report. This article was produced by the Course Report team in partnership with Thinkful.