Data Science is a growing career field that draws in bright and ambitious people for many reasons. For Phillipe Heitzman, it’s the opportunity to challenge oneself through tackling difficult business problems that first drew him to the field.
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“No data science problems are too similar. You approach each one as a fresh problem, using your skillset to get as close to the right answer as possible. It’s one of the more rewarding experiences, and intellectually stimulating as well,” he said.
Meanwhile, Douglas Pizac finds that being able to manipulate massive quantities of data and derive meaningful insights is important to create impactful decisions.
“It’s something I think is amazing, so that makes any kind of data science work I do all the more exciting.”
What do these two people have in common, beyond their love of data science? Both are graduates from New York City Data Science Academy, and both have gone on to have successful, exhilarating careers in data science after graduating.
An ACCET-accredited institution with a well-known reputation across the industry, NYC Data Science Academy is the common thread in many successful data scientists’ careers. Read on to see two different perspectives on the program, two paths toward NYC Data Science, and where these alumni ended up afterward.
NYC Data Science is a well-regarded bootcamp that challenges and supports students to build their careers in data science.Join the next NYC Data Science Academy cohort.
Before Discovering Data Science
Phillipe graduated from Duke University in 2019 and later that year, began working full-time on a credit structuring team at a large financial institution in New York. He’d taken a few computer science courses in college and dabbled in his free time, but he didn’t have much programming experience beyond that.
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The average bootcamp grad spent less than six months in career transition, from starting a bootcamp to finding their first job.
Douglas also had experience in academia. With a Master’s Degree in Biomechanics, Douglas pursued academic research after finishing school. His experience using data and programming to derive data in his research piqued his interest in machine learning.
“I realized I wanted to solve business questions rather than research-related ones.”
When Douglas decided he wanted to become a data scientist, he started teaching himself Python, R, and SQL in preparation for more serious training.
Phillipe, meanwhile, was realizing that while he loved working on the market side of financial services, he wanted more opportunities to work at the intersection of data analytics and business. Maintaining his full-time job, Phillipe decided to leap and enroll in NYC DSA part-time, online.
Douglas similarly decided to take the online program, and they both began their data science journeys.
Why Choose NYC Data Science Academy?
For Phillipe, choosing NYC DSA was a matter of flexibility. He had weighed a few options before finally enrolling.
“I remember considering two other bootcamp programs in my search,” Phillipe says. “But I ultimately felt that NYC DSA was the best fit from my own research. It seemed to allow students to learn both Python and R at the same time.”
It was one of the only programs to offer this when Phillipe enrolled. He also wanted to take the course part-time, allowing him to continue working. The last thing that sealed the deal for Phillipe was NYC DSA’s deep learning specialization, which he felt was a rare asset.
For Douglas, he chose the bootcamp because of its reputation. “I chose it because of how highly they rated, the impressive curriculum, and the opportunity to grow my professional network by interacting with my cohort.”
Douglas was accepted into a different data science program but felt that the NYC DSA program was the best choice to position himself in the field.
Mentorship and Supporting Your Career
Phillipe and Douglas both feel that the instructors and NYC DSA team did a great job creating an inclusive atmosphere and learning community with other students in their cohort. Whether it be Zoom catch-ups or office hours, there was always connection and support.
Phillipe says the school offered opportunities to meet one-on-one with alumni. This support allowed him to harness the knowledge of those who came before him. “It allowed me to get great feedback throughout my learning on data science work and career questions I had. It helped me tremendously in getting the most I could out of the program.”
He says the Career Services program helps students get as much exposure to the data science industry as possible. “They connected us with alums through the career portal, and made introductions through LinkedIn or email.”
NYC Data Science Academy also gives students opportunities to present their projects to alums and recruiters, which helps students get exposure, test their knowledge in a live setting, and provide the opportunity to communicate their ideas.
Phillipe notes that NYC DSA was very responsive to any requests he had, and any career or data science questions were quickly answered. “It was easy to get the support I needed. Knowing that you can reach out to alums and get connected is another great aspect of the bootcamp program, as looking at the alumni stories was very attractive to me as well.”
Job Search Assistance
Douglas says the bootcamp always offers external support from alumni. “While we were learning the basics, they walked us through what we’d need to expect in the job field and had alumni come and talk to us. Towards the end, they gave us case studies and had us rehearse machine learning theory and develop cheat sheets that would improve our candidacy.”
The job search was intensive, Douglas says, but worth it. It was like a full-time job applying to get a full-time job. He suggests students of the program listen to the job placement sessions again when they’re at the end of the program. He also praises the job placement tracker that NYC DSA uses as an organizational tool to keep students accountable for their job search.
“Having an order and structure really made the difference.”
An Investment in Your Future
Douglas and Phillipe agree that the tuition and time investment in NYC DSA is worth the while for those serious about pursuing data science as a career. Today, they work with some of the brightest minds in the industry.
“From a financial commitment to a time commitment, it was one of the best investments I’ve ever made, so I’m very happy with it to this day,” Phillipe says.
After graduating from NYC DSA, Phillipe went to work as the only data scientist on a small start-up team.
“From that experience of working in a more bootstrap environment and leading most of the data science work, it accelerated my learning journey. But I wanted to operate in a larger team environment in order to learn from experienced teammates.”
As such, he decided to go back to the top 50 financial fortunes company he worked for previously, this time as a data scientist. He now works there focusing primarily on predictive analytics projects for some of their core products.
Just two weeks after rejoining the company, he was assigned to lead a project, which he found a great learning opportunity, and incredibly exciting.
Douglas, meanwhile, leveraged NYC DSA’s large alumni network.
“Coming into a new industry, I knew my network was lacking, and part of the reason for coming to NYC DSA, besides its incredible curriculum, was to grow that network of professionals.” One of the alumni from NYC DSA referred him to a position as a data scientist consultant at Deloitte.
“I reached out to him on LinkedIn, saying I was an NYC DSA grad and I was very interested in the position. I ask[ed] if he could help me get my foot in the door [and] maybe look over my application. But he did so much more than that.”
This alumni coached Douglas through the interview process, passed his resume on to higher-ups, and helped him with a game plan. He ended up getting the job and now works at Deloitte.
Tips for NYC Data Science Academy Students
“If you’re seriously considering switching careers to data science while focusing on learning industry applicable skills as quickly as possible, NYC DSA is the best option to accomplish this,” Phillipe says. “Don’t be afraid to ask questions and try to get your hands as dirty as possible during the project work.”
He also urges students to take advantage of the school’s alumni network, by reaching out on LinkedIn and asking the NYC DSA staff to connect with you. “They’re extremely helpful throughout and willing to connect and assist with any career questions you may have.”
Douglas says that students should ask a lot of questions while in the course. “Try to ask questions and be as engaged as possible. But also try to pace yourself. It’s a marathon, not a sprint.”
It’s an intense amount of work, they both agree, but if you’re serious about data science, they also agree that it’s so worth it.
Are you ready to get to work towards an exciting career in data science? Follow in Phillipe and Douglas’s footsteps, and apply for NYC Data Science Academy’s next cohort here.
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