This November I am graduating from the PDEng program Data Science of the Technical University of Eindhoven (TU/e). For that reason, I am now looking into the next challenge in my professional life.
While searching for companies that make me excited these past few months I came upon Toptal. Toptal is a remote company that employs the best freelancers from all around the world. More specifically, the top 3% of freelancers, those who are able to get through its rigorous application process. The same holds true for Data Science freelancers.
I recently decided to apply as a freelance Data Scientist for the company. The remote culture, as well as the pool of top-notch companies and projects, fascinate me. As part of the application process, I am asked to write a blog post indicating the reason I believe I should be featured as one of Toptal’s Data Scientists.
Looking at the list of Data Scientists that currently are part of the Toptal network someone can only get overwhelmed. People from all around the world with years of experience and a long list of projects and skills on their profiles. The first idea that comes to mind is: how can I compare?
My Data Science Story
From the first look, I cannot really compare with many of these people. I lack the experience and the breadth of skills they do. I am also not a genius prodigy with numerous papers on their name.
For that reason, what I can only do is share my unique story in this Data Science road and the traits I have developed along the way.
Step 1: Engineering Depression
While in school I was one of the pretty clever students. I was also a quite nerdy, introverted guy who loved spending time on his PC. This combination led to me getting accepted to one of the most competitive engineering schools in Greece, the Electrical and Computer Engineering one at the University of Patras.
I cannot lie here. I am not the typical success story of an engineer who has been coding from 10 years old, has founded 5 startups in University, and soared through their exams. I was a guy who became overwhelmed with engineering and the rigorous demands of my University professors. Simple as that. That was at least the beginning.
During this time though, I was able to become knowledgable in blogging and Digital Marketing, making some money on the side through them. These skills, though not directly related to Data Science, have been helpful in their own way, for instance in creating this very blog you are reading now.
Step 2: Enter Machine Learning
When selecting the topic of my thesis I unknowingly made a very good decision. I chose something I was passionate about at the time, AI. I worked on academic timetabling using Machine Learning. This project was the one that gave me back my enthusiasm for engineering and development. This is also when I started loving Python.
Step 3: Enter Professional Doctorate in Engineering Data Science
After completing my Integrated Master Studies I was looking for the next bridge step to industry after University. This is the reason I applied for the PDEng program of the Technical University of Eindhoven, among candidates from all around the world. The program has a duration of two years and an industrial focus. I was selected among a very rich pool of candidates and a full-week intensive hackathon-like evaluation, where at the end of it we presented to the DOW chemical company. Among the six teams, comprised of both applicants and trainees of the program, my team won the first place in the challenge, voted by the company and University committee. This is a moment I am very proud of.
In the first year of the program, I had the chance to work for many team projects in the Dutch industry and work on their Data Science problems. Companies include ASML, Brabant Water, and Heijmans among others. I had the chance to develop technical skills and soft skills alike. I finished numerous online courses, coached new applicants to the program, coached professionals from the company Deltares, coached health professionals in the Data Science in Health professional education program of the Jheronimus Academy of Data Science, assisted my University supervisor in teaching the Introduction to Data Science course of the Technical University of Eindhoven, and came second with my team in a DeepFake-detection hackathon in Den Haag, built an analytical dashboard for the Dutch Military Museum with my team, built a Twitter Sentiment Analysis streaming dashboard for the Dutch Energy Transition, taught a workshop on building analytical dashboards with Plotly and Dash in Python for my colleagues, among other beautiful experiences.
In the second year of the program, I have been conducting a one-year full-time project for the Dutch National Police. Through this project, I have been able to see how to work for a real scrum team that works in an agile way. Moreover, I have had the need to balance the requirements of stakeholders both from the University and my company. I have had the need to be intrinsically motivated and independent in my work. I have had the need to facilitate and organize communication between different parties. I have had the need to document my results and progress clearly in written form.
Technically, I was able to specialize further in Deep Learning and Convolutional Neural Networks, Edge AI applications, Signal Analysis, and sensor systems.
Notably, along with my supervisor’s guidance, we have prototyped a novel way to classify sounds using a time-frequency distribution. I will be able to share more about that when I finish my project in November.
Bonus Step: Enter COVID-19
While working on my final project the COVID-19 pandemic started to unfold. Despite the very negative effect it had on life, it provided some hidden benefits to me. I had to work remotely and I started loving it. I do believe it has the potential to be the future of work. Moreover, the pandemic brought difficulties to data collection we were doing manually at the time. That pushed me to motivate myself, work independently, and finish a very interesting project on sound classification based only on open-source data.
What I bring to the table
Based on my above experiences, I have developed some qualities that I believe will serve me well as a Toptal freelancer.
- Ability to communicate clearly and effectively
- Management of multiple stakeholders
- Effective Presentation Skills
- Leadership skills
- Independence and Proactiveness
- Domain Knowledge from different companies and data science problems
Practical experience in many technical skills that are integral in Data Science:
- Data Analysis
- Machine / Deep Learning
- Time Series Analysis and Modelling
- Data Visualization
- Data Engineering
- Signal Analysis
- Web Development and APIs
- Software Engineering Best Practices
This was my Data Science journey up to now. In particular, the past few years have been incredibly productive and challenging in various aspects. I got exposed to so many facets in the Data Science and business world that I am really grateful for. Especially my time in the PDEng program Data Science has been one of the experiences in my life where I was able to build myself into a professional Data Scientist. For these reasons, I believe a company like Toptal is the next best step for me to challenge myself and improve my skills further. I may lack the huge experience of other Toptal freelancers, but I believe I can compensate for that with my enthusiasm, passion for Data Science and Machine Learning, and the combination of soft skills I bring to the table. Those are the parts of my Data Science career that I am really proud of up to now. We all have our small and big wins that make the journey worthwhile.