Alumni Spotlight

How This High School Teacher Became a Data Scientist after Metis

Jess Feldman

Written By Jess Feldman

Last updated on August 30, 2021

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Tim Dooley enjoyed teaching his high school students, but ultimately wanted a career that focused on unearthing exciting finds through innovative research. After some self-teaching, Tim enrolled at Metis’s full-time Data Science Bootcamp to learn everything from Python to data scraping to neural networks. Tim shares how the online community and dedicated career support at Metis made all the difference in landing his first Data Scientist role at Gartner!

What inspired you to shift from teaching and theology studies into data science?

I did a Ph.D. in my twenties and formed an understanding of how a language has the power to shape the belief systems that make humans who they are. After finishing that program, I found it difficult to find an academic job and I ended up teaching at a private high school in New York. Teaching was a wonderful experience, but I missed the research aspect of my work. I wanted to be making discoveries and communicating those findings to people. I became a dad last February and then COVID hit, and it felt like I needed to change up my career. 

I knew a bit of Python and it became a pandemic project of mine to learn more about data science and programming. I started looking into different data science bootcamps, using Course Report among other resources, and eventually decided on Metis.

What set Metis apart from other data science bootcamps during your research process?

When I was applying, we had no idea what the future was going to hold. Some of the bootcamps I was applying to said they would be switching back to in-person learning, but Metis made the decision early on to go fully online. The interactions that I had with everyone at Metis and the information that I read about them told me that they would be there to support student success. There’s no hand-holding, but they make sure that the best aspects of you are highlighted to advance your career in data science if you put the time in. Bootcamps are awesome, but they’re not a panacea. You have to put work in and at the end of the day, and it's a three-month commitment. 

What was the application process like for Metis? Did they give you any challenges to complete before accepting you into the bootcamp?

Yes, a bunch of challenges! I had some coding experience before this, and Metis tested me on my Python and math skills with practice tests in things like linear algebra, statistics, and some calculus. There’s also a hacker rank test and then the interview with an alum. Early on in the process, Metis also had me interview with a student that has already successfully gone through the program. I was able to talk with them about their experience, and I appreciated how frank they were. 

Do you feel like the Bootcamp Prep course was useful for you?

Totally. If you decide to continue on to the full-length bootcamp after completing their Bootcamp Prep Courses, the cost is deducted from the full course tuition! 

Did you receive any financing or scholarships from Metis?

I did not, but scholarships and financing are available through Metis. The Metis Scholarship is for underrepresented groups in coding, but there are also financing opportunities. Many programs will have different methods like an ISA or deferred tuition, but Metis was very straightforward with their payment options and that appealed to me.

What was a typical day like in Metis’s online Data Science bootcamp?

We would start with a pair-programming problem that got progressively harder as the course went on. It started with fizzbuzz and towards the end, you’re making Conway’s Game of Life from scratch or building algorithms from scratch with a partner. These exercises were a great way to learn to work collaboratively on coding and to meet with someone from my cohort for an hour. 

Next, we focused on projects. Throughout the bootcamp, we worked on a portfolio that we were building with five different projects. The first project was in a group and it worked as an icebreaker, but the other four are up to you within the scope of the project type. Metis teaches you how to scrape data early on in the bootcamp because you’ll have to scrape all of your own data for later projects. 

Then, we would work with our classmates who were doing something similar. For example, I was doing a project classifying beer based on recipes and they put me in a group with people that had projects based on wine and food. We could all bounce ideas off of each other which was awesome and a good way to build relationships with people I still talk to today. 

The afternoon was filled with lectures, which were intense. When you’re a student online, it’s harder to move around and make small talk. You’re on a schedule and you’re all there for one thing. The online classroom was a great way to learn and to have interaction with the teachers, and you have opportunities throughout the day to schedule meetings.

Did the online teaching style match your learning style?

The instructors at Metis are all awesome. They all have experience in the industry. Some of them are intense coders and could help us understand the theory behind why Python acts the way it does. Some of the teachers were math whizzes and were great at understanding and explaining concepts.

An important thing that Metis emphasizes in their teaching is that data science is a three-tiered approach: math, coding, and communication skills. If you come to Metis and you’re already decent at two of those subjects, the instructors can help you round out all three.

What did the bootcamp curriculum cover?

You start off with exploratory data analysis (EDA), Pandas, and basic Python packages, the essential toolkit for everybody. You pretty quickly break into linear regression and everything that comes with that. You learn how to scrape data so you can build your own projects. The curriculum also covers SQL, JavaScript, HTML, CSS, and NumPy.

Later, we started on classification where our target variable was a word. We learned about all the different types of classification and then we moved on to a project on unsupervised learning and natural language processing (NLP). That’s the big thing these days in tech and it’s 90% of my current job as a data scientist!

What projects did you work on in the bootcamp?

For one of my early projects, I scraped the website BoardGameGeek so I could make predictions about what a board game might be scored based on different factors.

I did my NLP project during the end of the 2020 election, so I focused on polarizing news headlines to try to understand if there were certain trends. I wanted to see if certain words like “fraud” showed up in the news months before the President started mentioning them, and also how one side of the media might talk about the election. As we learned about neural networks in the bootcamp, I built a text generator that could create fake Breitbart headlines.

The final project at Metis is based on our passion. I scraped the Bon Appetit website and made a project where you could take a picture of the food in your fridge and it would find a close recipe to the meal in your picture. You could also enter ingredients or a feeling and it would find you a recipe.

What was the online community like at Metis?

Metis set aside time for us to work together and I made a great group of friends. We worked collaboratively during the bootcamp, but also after I graduated, too, which was huge for me. Some of my cohort happen to live near me and I still talk to three of them weekly. It was great to bounce ideas off of one another. We were all lifting each other up. It got to a point where someone would hear about an interview, and if it wasn’t the right job for them, they would pass it to another person in our cohort and mention that they have a friend that would be a good choice. 

What has been the biggest roadblock in your career change journey?

Throughout Metis, you will hit hard times because it’s so much information at once. A person who barely knew Python a few weeks back is now trying to build legitimate artificial intelligence applications. In some ways, that’s a roadblock, but it’s a good roadblock! It takes a lot of strength to keep grinding and that can be tough. It’s kind of like going to the gym and doing an easy workout — If you don’t feel the burn, was it worth it? 

What kind of career support did you get from Metis?

You meet your career counselors in week one of the bootcamp and you connect with them occasionally during the bootcamp. You’re not pushing for a job yet when you’re in the middle of the bootcamp, but you should be thinking about it towards the end. 

After the bootcamp finished, I met with my counselor on Slack at least once a week and she was awesome. There are a lot of downs during the job application process, but when it rains, it pours. I had two awesome job offers that came in on the exact same day, and my career counselor gave me her number and let me call her so she could walk me through the offers. 

Everyone at Metis is doing their best to help you — Metis doesn’t guarantee you a job, but they’re confident you’ll get one if you finish the bootcamp.

What roles were you applying to after you graduated from Metis?

Data science jobs, for sure. The current industry has a weird way of wording this career and some of the jobs have funny names without data in the title, but they are all essentially data science jobs.

Congrats on your new data science job at Gartner! How did you land the job?

Gartner is the world’s leading research and advisory firm. They also consult and organize conferences. Most of the people subscribed to Gartner are in the C-suite level of their company. My current boss and a few other team members actually graduated from Metis, so that was helpful when I was applying. Companies definitely know the name Metis, and the association is positive.

When I was interviewing at different companies, my interview with Gartner was one of my favorites. Early on, I was hoping for some softball interviews, but Gartner’s was rigorous and I was drawn to that. It started with an HR chat and after that, I spoke to my current boss. I was given a big technical assignment that I had a week to complete. They gave me anonymized data and said to do something with it. I built models, digitalizations, and a deck. Once the week was up, I met with the Gartner team for four hours of interviews. After that, there was another meeting with HR and then I received an offer.

What kind of projects are you currently working on at Gartner? 

At Gartner, my work revolves around marketers, so most of the work that I do will end up in the hands of marketing leaders in global companies. Some of our stakeholders are small companies and some are fortune 500. I work for the QUADS team, which is quantitative analytics and data science. We analyze data and use machine learning to come up with groundbreaking research about marketing trends. 

My team has a product you can look at called Digital IQ, which talks about how savvy the bigger companies are. We look at companies to see how they perform with different benchmarks. I also do a lot of NLP, which involves a lot of text data. I spend much of my day analyzing and digesting that text data, so our researchers can produce research based on the models I built.

Are you using all of the languages and skills that you learned at Metis?

I use what I learned at Metis every single day. Data science is changing every single day, so really I think the biggest thing you can learn at Metis is how to learn. I use the fundamentals I learned from Metis, and it’s given me a framework to continue to learn, understand, and be part of the community.

Since you graduated, are you still connected to the Metis community?

Upon graduation, everyone is welcomed into the Metis Alumni Slack channel. I think it has one of the biggest alumni networks. I applied to many jobs I found on the alumni Slack, and I also  connected to my current boss through it. Alumni can ask each other questions and that education continues through Metis on Slack. This online Metis alumni community continues to help me learn.

You were a TA after graduating from Metis — What were the benefits of working as a TA before diving into your first data scientist role?

In addition to getting a paycheck while I was on the job hunt, being a TA was a great way to learn by teaching. At Metis, they would find problems I hadn’t encountered yet. You can learn a lot in three months, but you can’t learn it all. The nice thing about being a TA is that I kind of got to take the course again. It’s almost like watching a movie that you already love!

What is your advice for any teachers considering a career pivot into data science?

To any teachers out there wondering if data science is the right change for you, I think you’d be awesome in the field. Data science is like a teaching role because no matter where you get hired, the point of your job is to explain numbers and words so somebody who isn’t a data scientist understands. 

Looking back, was Metis worth it for you?

Absolutely. I couldn’t see myself being where I am without having gone to Metis. What you get from Metis is a world-class education in data science, which includes coding skills, programming skills, math skills, and communication, but you also get an unparalleled community and Metis attracts a special type of person. You also get that amazing career service and it goes hand-in-hand with the alumni network — Metis isn’t happy until you land that first job. I could still reach out to them and they would be happy to talk with me about my job.

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

About The Author

Jess Feldman

Jess Feldman

Jess Feldman is an accomplished writer and the Content Manager at Course Report, the leading platform for career changers who are exploring coding bootcamps. With a background in writing, teaching, and social media management, Jess plays a pivotal role in helping Course Report readers make informed decisions about their educational journey.

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