Expand Your Career Horizons at Explore @ 4

By Emily Young MA ‘16

 Have you ever heard of Big Data?  Big Data explains that with the world’s use of technology constantly growing, the mass amount of data we produce can be organized and analyzed for key insights. Yesterday at Explore @ 4, there was a panel of five data scientists working for various companies, Dun & Bradstreet, Verizon, Netflix, KIPP, and OpenX, who use data to solve business problems.

 Explore@4 is a series of career panel discussions hosted by the USC Career Center to help students explore different industries.  The panels are comprised of USC alumni in well-known and highly respected companies around LA.  Yesterday, the panel of data scientists was comprised of:

• Farhan Baluch, Senior Data Scientist at Netflix
• Ashley Luo, Data Scientist at Verizon
• Nicole Jeong, Senior Data Analyst at KIPP LA Schools
• Kyle, Asano, Business Data Analyst at Dun & Bradstreet
• Bilal Shaw, Data Scientist at OpenX

Key Takeaways:

 1) There are Different Paths to Becoming a Data Scientist, but Learning the Technical Skills is Key

 Big data is an emerging industry.  All five panelists graduated from USC within five years and used their degrees to gain technical skills, even if they were not in traditional data science majors. For example, Nicole, a Senior Data Analyst at KIPP LA Schools, wanted to do research in public policy and fix our education system.  She focused her Public Policy and Development Master’s on technical research skills and learned additional coding on the job.

Ashley, Data Scientist at Verizon, majored in Economics with a minor in Applied Math.  She thought she’d become an economist or go to Wall Street.  After her first internship, Ashley learned she liked data analytics.  She joined the USC Applied Statistics Club and learned various programs and coding. Her senior year, she did a data mining internship at Verizon and they hired her after graduation.

While neither Nicole or Ashley majored in Engineering or Computer Science, they both learned the technical skills to be a data scientist.  (See #3 Skills)

2) Predictive Modeling

Ever wonder what it would be like to tell the future?  Being a data scientist is like looking into a crystal ball, however they have to build the ball first. 

Predictive modeling starts with a business question.  What content should Netflix buy?  There’s a ton of data with thousands of variables to select from SAS SPSS modeling.  After you build a model you validate it with a random test.  Even if it seems right, you need to keep testing different variables because the Netflix budget for acquiring content is 4 billion next year.   One mistake could cost a million dollars.  At the end of the day it’s not what model you made, but how well you predict it. Bilal, Data Scientist at OpenX, shared, “don’t let the buzz words scare you.  Most marketing problems can be solved with linear regression and businesses like simple equations.”

3) Skills

Being a data scientist involves understanding a business problem, framing it mathematically, building and organizing a database to solve the equation, and then translating the results into a business action.  To accomplish this, there are several programs and languages that the data mining industry uses:

Learning 2/3 of these programs and languages is highly suggested along with competing in data competitions.

If you are an outsider to the computer science world like myself, that list may be a little daunting.  What is code? What is Python?

One of the panelist said, “if you can do nested “If” statements in excel, you can learn coding.”  To be a successful data scientist, you need to:  have great critical thinking skills, ability to frame business problems mathematically, work well in groups, and most importantly have curiosity.  

The great thing about the data science industry is that it is new age and there are so many ways to learn outside of formal schooling.  You can Google videos on Python software and learn through tutorials or take advantage of USC access to Lynda.  Even if you don’t have all the technical skills or formal schooling, the entire panel said it’s important to exhibit passion and curiosity on your cover letter.  

Furthermore, USC has an Applied Statistics Club for students interested in big data analytics and holds weekly workshops to build technical skills. https://www.facebook.com/uscappliedstats?fref=ts

4) You Need to go to Explore @ 4

At this point in time, I have no intention of being a data scientist, nor did I have any intention of being one before going to Explore @ 4.  However, listening to the panel for an hour was invaluable.  The role of data is growing across industries and for my career goals in marketing and branding working with data analysts is inevitable.  Having the knowledge of how they approach problems and form predictions will help me make more informed decisions and be a better team leader in the future.

It’s called Explore @ 4 for a reason.  I encourage you to check out the other two Explore @ 4 panels this week and the upcoming career events.

• Wed 9/9 Non-Traditional Careers for Psychology Majors (STU B3)
• Thurs 9/10 Math and Econ Careers (TCC 227)

~Emily