Javier Fernández Suárez

I'm a Data Scientist with experience building recommendation systems, Bayesian AB Test, in-depth product analysis using Python and SQL, Machine Learning models, Dashboard reporting, ETL systems like dbt_ and scheduling tasks with Docker microservices. 

My crypto story starts in 2019 when I bought bitcoin and ether. Sadly a couple of months later, I needed the money and I sold all, losing money clearly because I didn't know what I had. However, I did an epic come back in 2020 when I fell into the rabbit hole first of Bitcoin and later of Cardano. I started using Twitter again following lots of projects and influencers in the crypto world. I also spent quite a lot of time listening to podcasts and reading technical resources discovering how actually Proof of Work and Proof of Stake work. The more I was reading, the more I wanted to learn so I started to become an active member of the Cardano community while maintaining my taste for Bitcoin. I was lucky that at that time, March 2021, was when the NFTs arrived at Cardano so I also become a strong member of the CNFT community. I have minted most of the best projects including Spacebudz. At this point, I was all day talking about crypto and I created a group with friends to teach them about blockchain, which has been pretty successful. In 2022 a new adventure started for me with the pop up of the Cardano DeFi ecosystem. I created an arbitrage script and started doing yield farming. I’m passionate about blockchain: all the game theory, Proof of Stake, Proof of Work, smart contracts, the community, and our goals; make me feel that I'm living the best moment in history.

Now that you know how passionate I'm about crypto let's talk about myself and my other passion: Data. As you know blockchains are just decentralised databases so for me this couple does a great match. My first experience with data was at University where I had to create models that fit with the results of my experiments as part of my Physics degree. I chose to follow the computational path where I learned how to code in Matlab, C++, and Python, and I made several projects with these languages. One of the projects I enjoyed was using Python to work on chaotic particle dynamics in viscous flows problem.

My interest in data techniques led me to move to London and enrol in a data science Bootcamp. Learning from industry professionals, I built the ability to work with a wide range of data science tools. Here I worked on several projects using data cleaning and statistical modelling, including Machine Learning, in Python, as well as SQL, to prepare myself for a career in Data Science.

After completing the Data Science Bootcamp, I secured an offer to start working as a Data and Insight Analyst at Sportpursuit. The company is an online sports equipment marketplace where they use Data Science to improve marketing, change the website design, and grow the business. As part of my day-to-day job, I worked with large and complex databases (more than 8 million users), used Python and SQL, and ran A/B tests using a Bayesian approach. As an example, I ran a project using Python to analyse the number of sign-ups following a TV marketing campaign to decide on the most effective channel to reach clients. Finally, I was responsible for the Dashboards System migration from Board to Mode + dbt_.

I’m a curious person always looking for something new to learn. This led me to take my next career step seeking more Data Science theoretical knowledge. For this purpose, I managed to join as a Data Science Coach Flatiron School which was awarded in 2021 as the best Data Science Bootcamp in the world. This was a great movement that let me learn even more about complex topics such as Machine Learning and Hypothesis Testing. Daily, I was giving support to the students with Python, SQL, and git becoming a code debugging master. I also had the opportunity to learn about teaching and communicating by giving complex lectures about Classification, Regression, Clustering, etc.

On Flatiron, I mastered Data Science theory and I was ready for applying it with industry experience. My old company called me and I returned but this time as a Data Scientist. Here I have worked on a recommendation system, rebuilt the A/B test mechanism, scheduled complex workflows with docker, and in-depth analysis for the executives and product team for improving the website performance. In essence, I put to work all my theory knowledge on business impactful tasks which have made me greatly improve my business and product skills.

Now I want to work in the industry of my passion and I have started the Cardano Professional Developer Programme by Emurgo where I’m learning Haskell and blockchain technology.