Why I Decided To Become A Data Scientist
In 2013, I proudly finished my undergraduate studies in Petroleum Engineering from Texas A&M University. I went back to Angola (which is where I am originally from) and worked for the National Oil Company for 5 years as a reservoir engineer. In the meantime, during those 5 years, I also got my maters in Project management from the University of Liverpool and a post graduate degree in Business Administration from the Lisbon Catholic School. At the end of those 5 years, my family was given the opportunity to move back to the US as residents, and we decided to embrace it. I also decided to not pursue my career as a Project Manager and just continue my career as a Petroleum Engineer.
While applying for jobs, I decided to use the rest of my free to learn a programing language. I took the python bootcamp course from udemy and to my surprise, I more than liked it. I then started looking into ways in which programing could add value to my petroleum engineering career, and the field that really got my attention was data science. While my job search for reservoir engineering positions was not being successful, I found out that according to Glassdoor, since 2016, data science has been identified as the job with the higher career opportunities, with a rating of 4.3 out of 5 and about 6,500 job openings this year.
What is data science?
Data science has been defined by techterms as the study of data, consisting of recording, storing and analyzing it to then draw insights from it. According to Joma, a software engineer who used to work as a data scientist for Facebook, there are three main types of data scientists:
1. Data analystis which are the ones that look at data, do some queries, process it, make graphs and then communicate their findings to product managers.
2. Data engineers. Retrieve the data and build the infrastructure so that we can then look at the data.
3. Data science core. These are usually people with PhDs that build recommendation models and perform forecasting.
I am looking at exploring either one of the first two options.
Why is data science a field that interests me?
First, data science would add value to my Petroleum engineering career. As a reservoir engineer, I spent a lot of time working with data, making proposals to acquire data, working with models and making production forecasts. In this type of conventional studies, “data is not there to help understand the physics, but rather, data is there to help us model the physics”. This means that we are not starting our analysis with the equations, we are starting with the data. This new approach, gives hopes to help decrease some uncertainties in the results obtained from reservoir engineering studies(SPE).
The second reason why I am interested in the field is that it would give me the flexibility to change into a different field, if I feel the need to, while still doing what I enjoy doing which is analyzing data.
References
https://techterms.com/definition/data_science
SPE Bookstore: Data-Driven Reservoir Modeling