We thank Rafael Carlos Cerutti De Oliveira, Solutions Architect at iMerit Technologies for taking part in the Data Science Leaders interview series.
Academic Background
Bala: Could you tell us about your academic background?
Rafael Oliveira: I have a Bachelor’s in Computer Science from the Universidade Estadual Paulista (UNESP), and a Master’s degree in IT Management from Fundacao Getulio Vargas (FGV) both in Sao Paulo, Brazil. I also have an MBA from Hult International Business School, San Francisco.
Getting into Data Science
Bala: When did you realize that you should pursue a career in Data Science?
Rafael Oliveira: When I was pursuing my MBA, I developed an interest in Data Analytics and started networking in meetups and events in the area. This helped me in connecting with Data Science communities and folks who were also interested in working with data. Consequently, I joined Open Data Science Inc. (ODSC). At ODSC, I had the opportunity to connect with many companies including iMerit, experts and Data Science enthusiasts across all industries. This was important in shaping my career in Data Science. Seeing everything that AI and Data Science are doing for the world in multiple industries such as healthcare, finance and mobility made me excited to be a part of this “thing” that is shaping the future.
Bala: Could you tell us about your current role as a Solutions Architect at iMerit Technology?
Rafael Oliveira: iMerit is a combination of technologies, processes and people to create end-to-end AI data solutions that deliver the highest quality data in the industry. Technology is always an important factor in our solution, but the expertise we provide in different industries, annotation tools and workflow design are what clients value most in supporting their computer vision models.
As a Solutions Architect, I help our clients design the best solution to provide high quality annotated data, translating their needs to real systems that take care of the sourcing, processing and delivery of the annotated data being that from text, audio, videos, lidars, etc.
Democratization of Data Science
Bala: Could you tell us about the democratization of Data Science? Rafael Oliveira: In my opinion, we were forced to live in a new environment due to the pandemic, which accelerated the democratization of Data Science. More and more content has become available and a lot of it is free. There is a shift in the market where companies are working to create a community around their content; they see the value in educating end users, not just the person that signs the contract.
This is opening many doors – from providing access to products and technologies at low or no cost to expanding to until now unexplored markets to let users test platforms, and really understand if that is what they need before they buy it.
I see companies and training platforms being key players in the democratization of Data Science and AI.
Advice to Aspiring Data Scientists
Bala: What is your advice to those looking to get started in Data Science? Rafael Oliveira: I would suggest keeping the following key points in mind:
- Don’t think you will learn everything in 30 days. Good data scientists, data engineers and any other technologists have studied and worked hard and for a long time on what they do.
- Get your “hands dirty”, the theory is fundamental but look for places where you can do hands-on projects, practicing is fundamental. Look for instructors that get you involved instead of just talking, look for code challenges and projects to do individually and with peers.
- Don’t try to know everything, choose a path. Do you want to be a machine learning or deep learning expert? Do you want to become a master in Data Visualization and Storytelling or do you want to know NLP? Data science is very broad, you have to choose the game you want to play in and dedicate heavily to it.
- Don’t skip the basics and the foundation. Math, statistics and at least basic knowledge of programming and tech infrastructure are mandatory. Do understand and study some cloud fundamentals, SQL, etc.
- You don’t necessarily need to be a Data Scientist to be involved. You can work as a data engineer, solutions engineer, solutions architect, and much more. Even Product Manager and other less technical roles (in some cases) are a key piece of AI and Data Science nowadays.
Bala: Could you suggest learning resources that would help aspirants to gain foundational data skills? Rafael Oliveira: aiplus.training – This platform really provides a great amount of resources from true experts. In addition, you can follow the blogs below for daily and weekly fresh content:
I also suggest that you start following some influencers on LinkedIn, or experts in the Data Science field you are interested in learning from.
And never forget how fast the technology field evolves. A good professional will keep up with the market updates, new companies, new frameworks, etc.
Skills and Traits of a Good Data Scientist
Bala: What skills and traits do you think a good Data Scientist should possess? Rafael Oliveira: In my opinion, the following are the necessary skills that any candidate should try to master.
- Math and Statistics
- Proficiency in a programming language, such as, Python or R
- Basics of Data Science and AI From here, it is important to understand what you want to go deep into, such as Deep learning, NLP, Machine Learning, Computer Vision, etc. Depending on your choice there are many other necessary skills
Bala: Could you tag a few guests that you’d like us to feature in this interview series and you recommend aspiring Data Scientists to follow?
Rafael Oliveira: Sure, I would suggest the following guests who might as well be featured in this series. At iMerit, we have great experts in multiple fronts.
- Lauren Robinson – Director of Customer Solutions at iMerit
- Sina Bari – Director of Medical AI
- Mallory Dodd – Solutions Architect and Specialist in Geospatial Technologies
- Jonathan Kurniawan – AI Consultant
- Leonardo Santos – CEO of Semantix
Finally, I would like to share that iMerit is hiring for many positions across all teams. You can head over to our careers page to check all the currently available openings.