We are constantly growing at Santander Global T&O and new positions are popping up in the IT world almost every day. Data Science is an interdisciplinary field that employs scientific methods, algorithms, and other advanced techniques to identify insights and patterns hidden in data. It also relies on Big Data to analyze large volumes of data as a means of facilitating business decisions. However… that’s just a glimpse of what a Data Scientist does. Do you want to learn more?
The main areas of Data Science teams include Data Science, Data Engineering, Data Analysis, Machine Learning Engineering, and Software Engineering. These require profiles that include people with mathematics, statistics, and engineering backgrounds, among others.
Juanjo Prieto works as a Data Scientist with the Global Cyber Security team and recently joined Santander’s community of technology experts, SanExperts. Would you like to know what a Data Scientist does at Cyber?
1. How did you get to where you are now?
If I had to summarise my career path, it would be something like this:
I studied Mathematics, but I always liked its practical application to real-life problems. I joined the Non-Financial Risks area of the Bank’s Internal Audit Department, more specifically Technology Risks, Data, and Cyber Security.
I’ve participated in important projects across the Group relating to data and technology, which has even seen me travel to other countries (Hong Kong, the UK, etc.). This has given me a cross-cutting vision of the technology platforms and data architectures that support these business processes.
In addition, as a Data Scientist under the transformation plan, I developed products based on big data analytics, machine learning, blockchain, and so on to digitalize functions.
I’ve learned from launching start-ups based on artificial intelligence, APIs, blockchain… During the pandemic, I worked together with the Ministry of Health of Castile and Leon to develop a SIR-type epidemiological model to understand the spread of COVID-19.
2. Can you also tell us what a Data Scientist does in the field of Cyber Security?
That’s a very good question and I’ll see if I can answer it but basically, it’s all maths!
Everyone knows the Cyber world is very dynamic and the bad guys are constantly looking for new ways to attack. That’s why the way we defend ourselves must also evolve.
While we used to rely on signatures and static rules to detect possible attacks, we now require a more scientific approach to search for patterns of behavior. Add to that the vast amount of data we receive daily for analysis and you have a better idea of what we do.
At the end of the day, it’s all about improving detection capabilities by applying AI, machine learning and Big Data techniques.
3. It sounds like a major challenge; what motivated you to make this change?
The truth is that previously I was in a very comfortable position with plenty of visibility and projection. It was undoubtedly my curiosity and keenness to take on new challenges that prompted me to take the plunge.
As a Data Scientist, the main things you need to successfully undertake data-driven projects are:
- Large volumes of data.
- Adding value to business problems by applying Advanced Analytics.
- Support from Management.
All these elements were present in my case. As you yourself said, it’s a major challenge with much to be done and we’re at a very early stage of maturity right now.
“Data science, the eyes of the cyber security sword.”Data Science for Cyber Security
4. What are the differences when working in a 100% technological company like SGT&O?
To be honest, in reality, there isn’t that much of a difference in cultural terms. Santander’s technological transformation is a fact.
It’s true that now I’m in a more creative and innovative role that is closely related to the world of development, in our case the development of products based on these types of techniques.
One difference might be the speed and agility when undertaking any project
5. And the main challenges of overseeing data projects at Cyber?
I believe they are no different from other sectors which are at an early stage of implementation of data science projects.
- I would highlight that due to the sheer volume of data, scaling all these techniques to process them in parallel will be one of the biggest challenges. It’s not the same to carry out a small project and run it on your laptop as it is to run it for terabytes of data distributed in a Big Data cluster.
- Another challenge we face in general with anomaly detection models is the need to add layers of enrichment and ex-post intelligence in order to deliver more robust end products.
- Finally, and this could be the topic of a post of its own 😉, we need to measure the return on investment of these types of projects. This is a challenge we face in the industry for products that are not linked to increased profits or optimizing costs.
6. Finally, what advice would you give to new recruits?
Well, I think I’m years away from being able to give any advice.
However, there are certain values I hold dear: a passion for what you do, curiosity, and a boundless desire to learn, but above all the importance of being a good person and working as part of a team.
Santander Global T&O is a global company of Santander Group with more than 3,000 employees and based in Madrid, we work to make Santander an open platform for financial services.
Check out the positions we have open here to join this great team and Be Tech! with Santander.