Posted by Pranjali Galgali
Updated: Apr 4, 2019
In the fast-paced world of data science, you need a little more than technical skills to transition from being a student to being hired. Networking in the data science industry, tapping into the opportunities, and making the right connections can play an extremely important role in achieving career growth. Besides having genuine interest and expertise in their field of study, it is important for those looking for jobs to maintain mutually beneficial relationships with classmates, employers, and colleagues.
NYC Data Science Academy (NYCDSA) Alumnus Kweku Ulzen knows firsthand how networking and building relations can help data science professionals find new opportunities in the field. As Kweku explains, “The purpose of networking is the exchange of information, advice, and referrals, via the informational interview process, to assist in attaining your goal of changing careers.”
Kweku is an alumnus of NYCDSA’s June 2018 cohort and is, currently employed as Senior Data Scientist with Nielsen. It was Kweku’s network that helped him learn about NYCDSA and ultimately build a career in data science—he was referred to the program by another NYCDSA alum, Mike Chuang.
NYCDSA helped Ulzen pursue his love of of technology and data, and during the program, he explored how the two intersect to affect society. Learn more about Kweku’s experience at NYCDSA in the video below:
Kweku was excited to explore new opportunities at NYC Data Science Academy, including the collaborative projects he worked on. The project on ‘Predicting Home Prices in Ames, IA Using Regression Models’ helped him to network with his classmates, develop technical skills, and get the support needed from his mentors and peers that pushed his career forward by providing additional value to his future customers.
“I had the pleasure of working with many different people during my time at the NYCDSA, and during that time I had to learn how to work efficiently with everyone. I have the ability to quickly gauge the work styles and personalities of others, and I can adjust my own style to work seamlessly with theirs. I find that this makes working on a team much more productive because I am able to quickly build rapport with team members,” he adds.
He was a part of the 12-week Bootcamp that teaches the full set of tools necessary for a data scientist to hit the ground running in his/her first job. Unlike other programs that focus on one language or one set of tools, NYC Data Science Academy teaches all the technical skills that employers are looking for, including R, Python, Hadoop, and Spark.
Aside from being part of a network, it is important to put 100% effort into your projects, connect with your peers to understand their unique backgrounds and perspectives and ask the support from the instructors. Apart from these students should actively engage in:
Meetups: These are a great way to meet other data scientists and discuss opportunities, trends, and events in the field. Some meetups also offer training workshops for data science and analytic teams.
Social Media: Being present on Twitter, Github, and Kaggle, and promoting/discussing your work with your peers is a great way to network with like-minded people. It is a good idea to be part of LinkedIn groups, webinars, tweetchats, and Quora discussions.
Networking/Hiring Events: Sign up for networking opportunities and hiring events and feel free to talk about your real-world projects, discuss challenges, and share your aspirations.
Not only are big data and data science exciting and growing parts of the tech industry, they are also an invaluable boon to the corporate world. Today, thanks to the worldwide community of data scientists, new tools have been developed that let us use information in ways we never thought possible. Whether you are trying to learn the enterprise applications for a Hadoop cluster or just want to learn the basics, NYC Data Science Academy has something to offer you.
They don’t just teach our courses here at NYC Data Academy– they live them. Our courses are made and taught by industry leaders and experts. We challenge traditional data analysis thinking as we inspire and train the next generation of data scientists and data visualization professionals.
Pranjali Galgali is a Marketing and Communications Associate, NYC Data Science Academy. She is a Master's in Digital Media and Strategic Communications from Rutgers University. She enjoys reading and writing about data science, upcoming technologies and loves interviewing people.View all articles
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