Springboard has recently launched a Data Science bootcamp with a job guarantee. We sat down with Adarsh Srinivas, an alum of Springboard's Data Science Intensive, to learn more about his experience.
While working toward his Master's Degree in Information Systems, Adarsh became passionate about using data to help companies make smarter decisions. He started searching for an intensive, mentor-led program that would give him the skills he would need to pursue a Data Science position after graduation. Springboard seemed like the perfect fit because it offered the kind of one-on-one support that other online programs lacked.
In an interview with SwitchUp, Adarsh talks about what he loves about Data Science, his experience with Springboard, and how the bootcamp prepared him for his new role in Data Analytics at Ernst & Young.
1. Tell us about your background. What was your education and professional experience before joining the Data Science Intensive?
I have a Bachelor of Engineering in Electronics and Telecommunication. I came to the United States in Fall 2015 to pursue my Masters in Information Systems specializing in Data Science from the University of Maryland. In my Master's curriculum, I had exposure to statistics using SPSS, database design using SQL, and a bit of R programming. A year into my Master's degree, I started exploring options to learn data science skills that were not covered in my coursework. I also interned at a tech startup in Los Angeles during Summer 2016 and thought that learning Python would allow me to implement some cool stuff at work. A Python Data Science course was not offered in my Master's curriculum, so I decided to learn those skills with Springboard.
2. How did you become interested in Data Science?
In the first semester of my Master's degree, I took a class in Statistics which involved different statistical tests, interpretation of statistical findings and statistics for data analysis. I was so intrigued and interested by how data analysis could be used to help solve business problems. There are large volumes of data everywhere we go, but not many people have the skills to make sense of it. I became passionate about helping people make smarter decisions by leveraging their data. I developed an interest in finding useful information hidden in the data, and I decided to pursue Data Science as a career.
3. What made you decide to enroll in Springboard's Data Science Intensive? Why was this program the right choice for you?
When I was exploring Python-related courses, I came across a number of courses offered by Udemy, Coursera, and Edx. I was browsing through Facebook and I came across the Springboard ad in my daily feed. Almost everything I saw on the Springboard website caught my attention and was different than the other options I was considering. I could see the entire curriculum, and just by looking at the website, going through alumni testimonials, and going through reviews, I trusted the program.
I ultimately chose Springboard because of the unique opportunity to work with a Data Science Professional (mentor). The fact that Springboard issues a certification also helped, as that was something that I could add to my resume while looking for jobs. Finally, the capstone project was a huge plus, as it enabled me to develop a portfolio, work on a real-world project with an industry professional, and market myself to potential employers.
4. Tell us about your experience in a remote bootcamp. What do you think were the pros and cons of a remote program?
I had tried other online educational websites such as Lynda.com, Edx, Udemy, and Coursera. Though all these courses helped me in a lot of ways, they did not provide me with a "one-stop shop" for everything related to Data Science. Springboard provided me with a Data Science Certification, which I couldn't find through other online schools. Also, no other program had this style of mentor-led workshops and a capstone project to work on. The amount you can learn when working with a real-world industry professional on a capstone project is incomparable.
My overall experience in a remote bootcamp was very positive. Springboard makes learning very easy through its online software so that it feels like an "in-person" program. The Slack community and the office hours add a human touch and allow you to interact with people to solve problems. The mentor call via video means you get to share your work and get feedback, like at an in-person bootcamp. Because of this, I did not find there to be a lot of the cons that you might find in a typical remote bootcamp.
5. What challenges did you overcome to get where you are?
My main challenge was transitioning from a core Electronics/Telecommunication engineering field to Data Science. I had to learn statistics, databases (SQL), predictive modeling, machine learning, and data visualization, as well as technologies such as Python, R, Tableau etc. This required immense determination and a huge time commitment. It is a process and you can only get there one step at a time. Another challenge was landing a Data Science internship, as that's typically the best way to break into the field. Once you intern and get a hang of the role and tasks, it is easier to sell yourself and get a full-time job offer.
6. Tell us about your career now. What are your goals and plans for the next few years?
I am employed in the Forensic Technology and Discovery Services (FTDS) practice of Ernst & Young in Washington D.C., which is basically the data analytics arm of EY. My role involves performing data analysis to find patterns and analyze trends related to money laundering, embezzlement, bribery & corruption, cyber breach, identity theft, insider threat, and employee fraud. Our clients are giants in various industries such as Pharmaceutical, Oil and Gas, Financial services, Retail and Consumer products, Technology, Automotive, etc. The work is quite impactful and directly related to my interest in Data Analytics. My plan for the next few years is to gain experience in this exciting field, learn and acquire more Data Science skills through the EY career development program and eventually become a manager in this practice.
7. How do the skills you learned at Springboard factor into your day-to-day work as a Data Scientist?
I have learned the entire Data Science lifecycle process through Springboard. This is helpful as a lot of my projects for clients are purely data analytics. To delve deeper, Ernst and Young's data analytics projects involve extracting data using SQL, cleaning and manipulating the data, conducting descriptive statistics, finding patterns, and visualizing the results to help clients understand the data and make decisions. Each of these aspects was covered through the Springboard curriculum. Now that I've experienced Data Science work in the real-world, I can confidently say that Springboard prepares you for the industry and covers all aspects that you would need to be employed as Data Analyst/Data Scientist.
8. What advice do you have for students who want to learn Data Science?
For anyone considering Springboard, the Data Science Intensive curriculum prepares you completely for the industry. The support structure provided by Springboard, from the student advisor to your mentor, is amazing and Springboard does all it can to help you go out there and be successful.
For anyone considering Data Science as a career, it is important to build a good portfolio that you can showcase to potential employers, and work on a number of projects to get hands-on experience. You should also network with Data Science professionals, work on projects with mentors, and have a genuine curiosity for the field as there is so much you can learn. Otherwise, knowledge of statistics, machine learning, and effective communication helps greatly during Data Science interviews.
We leave traces of data everywhere we go, so there is a need for professionals who can make sense of the numbers and consult on business decisions. There is a shortage of qualified Data Scientists in the market right now, and this skill set can put you in high demand in a competitive job market.
To learn more about launching your Data Science career, check out Springboard's Data Science Intensive.
