I am a data scientist who enjoys playing with data like a Lego game. I break it into pieces, rearrange, and create something new out of them. Well, this is what I am and what I do, but if you wonder how I become a data scientist, keep reading.
I graduated from Marmara University as a computer engineer in 2013. After my graduation, I decided to take my education one step further. In the same year, I was accepted by Dalhousie University for Master of Computer Science graduate program. So, my journey in Canada started in Halifax, NS.
In the first year of my graduate education, I took four courses related to machine learning and big data. They opened a whole new world for me. Until that time, I haven't realized the importance of data, and how machine learning helps us to understand it better.
Fortunately, I had the opportunity to put what I have learned from courses into practice. In my second year, I was accepted to Mitacs Accelerate research internship program. The aim of this program is to bring industry professionals and graduate students together and provide funds for real-world research projects. I worked in collaboration with GTECH, one of the largest lottery and gaming companies in the world, to solve one of the well-known CRM (Customer Relationship Management) problems, churn detection/prediction.
After eight months of successful research and development process, I have gained experience in various statistical and machine learning tools. I get my hands dirty with a high volume of data and lots of code. Finally, I presented the research details with a paper in Discovery Science 2015 conference. At the end of the day, I knew that data science would always be a huge part of my life.
Now, I am in Toronto and looking for the next big challenge.
Cheers!
The goal is to turn data into information, and information into insight.
State-of-the-art clustering algorithms developed for Evolutionary Computation and Big Data analytics. Reengineered Flockstream, a bio-inspired algorithm to use on predictive analysis of continuously streaming data. Prepared a comprehensive technical report to present the new version of Flockstream achieving 93% purity to detect churners, which is up to 43% higher than the successor algorithms.
Assisted professors in developing the curriculum, support materials, tutorials and design of weekly presentations. Taught various network security tools such as Wireshark, Snort, Nmap, and Ntop. Tutored students to solve both technical and conceptual problems related to operating systems and tools. Marked presentations and assignments.
Used several Java technologies such as Hibernate and Spring.
Instructed lab sections once a week in fall and spring semesters. Prepared presentations and code samples to help students better understand and practice Java. Marked assignments, quizzes, and term projects.
Communicated with the company’s customers when they encounter any problem with the mobile sale and distribution program, named EnRoute Panorama, and solved them by using remote access.
Researched integration and usage of web widgets on smart TV’s and prepared a report for the team leader.
Torture the data, and it will confess to anything.
