Among one one of the most frequently asked questions
by prospective students in graduate school info-sessions
is, "Why should I get an M.S. in Analytics?" There is no doubt that Data Science is highly in demand, but the field really made waves this year when it won Glassdoor's number 1 position
on its 50 Best Jobs in America
for the third year in a row. Using analytics, IBM has predicted that job growth for Data Scientists and Advanced Analytics will climb by 28%
by the year 2020. If you're reading this and thinking "Great! Where can I sign up
?", then you might be the kind of data-driven person who would be a great fit for a career in data science.
But getting a foot in the door is not without its challenges. If you're trying to break into the field, I've been there and I know what you're thinking. Data Scientist, Data Engineer, Data Architect, Data Analyst, Business Intelligence Analyst, Programmer Analyst, Statistician
... Are they even related?! What's the difference besides the average salary? This distance Ivy League certificate program promises that I could jump-start my career at a fraction of a cost in the convenience of my own home. (Quick tip: usually you can audit those courses for free if it's not offered by a 3rd party.) Why do I need a Master's, and why should I choose Texas A&M University out of all the options out there? I recently discovered The Data Science Handbook
by Field Cady. Criticisms of the book include that it is "three miles wide and three inches deep." And while I agree that he does not go in depth, it is great for giving people an introduction to the field. Many of our M.S. Analytics graduates become senior data scientists or data engineers. I was really surprised to learn that some of my classmates didn't want to be data scientists, and they just wanted to improve their skills as analysts or consultants.
"Data science means doing analytics work that, for one reason or another, requires a substantial amount of software engineering skills." - Field Cady, The Data Science Handbook
Data Science at TAMU
There are essentially 4 paths to data science at Texas A&M alone. The M.S. Analytics program goes deeper into Business and has a good balance of Statistics, but you will not get past beginner level in computer science without self study. This makes the program a great fit if you have a computer science background.
However if you already know that your domain expertise is in finance, or if you just really love stochastic processes, M.S. Quantitative Finance
may be a better fit for you.
The most traditional / common route to data science is through statistics. This is an excellent choice for students with an undergraduate degree in computer science, but keep in mind that only the applied statistics track is available through distance education. M.S. in Statistics.
This is also a great option if you are considering pursuing a PhD.
Last but not least, you can choose to go deep into computer science with out Department of Electrical and Computer Engineering.
This is best for students who are interested in High Performance Computing or pursuing a PhD.
Why You Should Get a Master's
"Nothing in the world is worth having or worth doing unless it means effort, pain, difficulty..." - Theodore Roosevelt
Word on the net is that the market is just flooded with junior talent. The truth is, regardless of scarcity
employers are not looking to hire candidates who do not have qualifications. To make things worse, I know I've personally experienced strange gap where employers won't take an intern unless you're a fresh graduate but won't take an entry level unless you have 3+ years of experience.
Employers often request fewer years of work experience for those who hold a Master's degree. I have lost count of the times I have seen the words "Master's degree preferred," but I have yet to see a single job description with the words "Boot camp certificates accepted," or "Boot camp can replace equivalent work experience." Choosing a program can be difficult and with tuition rates in the tens of thousands of dollars, it can be a highly risky
But even universities boot camps can't be trusted. Certificates offered by universities sometimes aren't even supplied by the institution themselves and should not be confused with a graduate certificate granted from upper level courses. I'm not naming names but if you look closely sometimes you will see "bought to you by (3rd party company)".
I have researched a lot of programs, and there are two big things to watch out for. First, if they program doesn't offer up any information (curriculum, tuition) without asking for your e-mail and phone number proceed with caution. Secondly if you do not know who is teaching the courses, or if the course is not taught by verifiable professors or industry experts, stay away. These 3-9 hour certificate programs can run up to thousands of dollars but do not bring you any closer to a full Master's degree. Because these programs are not accredited, getting financial aid or employer support is extremely difficult.
A personal anecdote, am a part of the 2020 cohort. I found and applied for TAMU Analytics
because I was not where I wanted to be in my career
and knew I needed to make a change. Just putting my acceptance into the program on my resume landed me a job with a 30% salary increase. During the interview my current employer was very interested in the capstone project, which has a very real economic impact for companies.
Ask us more about Data Analytics in our next info-session
. Join us for dinner locally in Houston at the May's at CityCenter or Zoom in remotely to learn more about the program and how you can get a head start on the hottest career of 2018. Texas A&M University Analytics program admits on a rolling basis
but class sizes are limited. For more upcoming events like us on Facebook
, follow us on Twitter
, or connect with us on LinkedIn
. See you soon!
Jennifer is a Masters student in the College of Science's Analytics program.