I became interested in Data Science when I came across the now famous 2012 Harvard Business Review article "Data Scientist: The Sexiest Job of the 21st Century". As I was reading the article I thought to myself "I wanna be sexy too"!!!! The article details the career development of Jonathan Goldman at LinkedIn . How his idea to create a custom ad display to link members with 3 individuals they may know but haven't connected with and evaluate the data generated via the click selection. Well those of us who are apart of the professional social network know how much we now utilize this staple feature of LinkedIn. This was the beginning of the role called Data Scientist. Fast forward to 2015, the desire to find individuals who can fill this role effectively is becoming a great concern. "The shortage of data scientists is becoming a serious constraint in some sectors".
The article continues by detailing "What qualities make a data scientist successful? Think of him or her as a hybrid of data hacker, analyst, communicator, and trusted adviser. The combination is extremely powerful—and rare." Currently the ability to write and understand programming and software engineering principles are the most common skill set. While this is not easy to attain it pales in comparison to the evolving need for Data Scientist to be able to communicate their findings via a storytelling effectively.
"George Roumeliotis, the head of a data science team at Intuit in Silicon Valley" states that the background he looks for when interviewing potential Data Scientist is "a skill set—a solid foundation in math, statistics, probability, and computer science—and certain habits of mind. He wants people with a feel for business issues and empathy for customers. Then, he says, he builds on all that with on-the-job training and an occasional course in a particular technology."
If you've made it this far into my boring blog you could be asking yourself "WTF! Is this guy really going to bore me to death with a book report about a HBR article????" Well yes and no. The purpose of this blog series is to give a look into how I made the career transition so I could be sexy too!
Obviously I decided that this is the direction I need to take my career. A little about my background. I am the eternal student with MS in Computer Science a MBA in Finance, and currently pursuing a Doctorate of Science in Computer Science. I'm also transitioning from working for a software consulting industry leader as a Software Architect and Tech Lead to starting my own consulting firm where myself and a good friend providing services as subcontractors in the same industry.
Naturally after reading the HBR article I was pumped. I just knew that I had the academic and professional background to EASILY transition into a Data Scientist role. Well I was right and wrong. I do possess the disparate skills needed to perform the tasking a Data Scientist faces, but I didn’t have the holistic understanding of the process of data science.
So how do I get over that hump? How does one get the necessary experience to qualify for a job in a field that is still new but all the job description requires 7 years experience? Well you could take the Cousera certificate in the advanced track of Stanford’s online Machine Learning course. Or you could join user groups devoted to data science tools to acquire training. Or you go back to school or a training program. So after doing a search, realizing that there are several schools starting Master's degrees in Data Analytics (but I have enough Master's), immersive training programs in which I would have to give up my income, move to New York city and pay huge amounts of money to be trained by experts in the field or attempt self study and contribute to a series of open source projects (yes I know this is a run on sentence); I decided to attend a graduate certificate program I discovered taught at Georgetown University in Data Science.
Over the next few weeks I will share an overview of the topics I had the priviledge learning from a diverse set of instructors. By no means do I feel I’m an expert in this field (not quite yet) and no way will I be able share in-depth the material I learned; but I do feel I can provide an overview of the general process of Data Science. From Hypothesis to Storytelling, Machine Learning to Descriptive Statistics, I will attempt to foster the curiosity of the newbies like myself and share my interpretation of the viewpoints of my esteemed instructors. In the end I hope to show how fun Data Science can be and also do my instructors at Georgetown University proud.
Additionally I hope to give a look into my entrepreneurial journey as I start my company!!!!!!! Thank you all for going on this geeky ride with me.
