Ariadna Fernández is a data engineer at Hosco, Barcelona. In 2020, she participated in the Data Analytics and Machine Learning bootcamp at Ubiqum Code Academy, an academy that offers different coding bootcamps based on the learning by doing methodology. In our interview with Ariadna, she said the thing that struck her most was the diversity of jobs available in the field –in many respects, data goes far beyond computing.
Banking and insurance companies have been relying on data to inform their decisions for decades. But now, it seems like every industry is benefitting from big data to get ahead of the competition: from healthcare to travel, retail to entertainment, every sector is looking to big data to develop better products and services.
However, this isn’t to suggest that data alone is the key to success. It’s not good enough to just collect data –you need a team of people who know how to interpret it. Being able to work with data and draw out actionable insights is crucial for modern companies –and those who can do it are in high demand.
“I learnt to use a lot of useful tools, like Python and Tableau, all of which can be adapted to the job market we have nowadays”.Ariadna Fernández
It’s clear now that many jobs are being replaced by machines. With self-driving cars, almost human-level translation tools, and automatic call centres, artificial intelligence and machine learning are eating away at the job market as we know it.
That is why the recent boom in data analysis jobs couldn’t have come at a better time. With so many jobs inevitably going to the machines, professionals can upskill so they’re the ones writing the code behind the algorithms. Furthermore, bootcamps like those managed by Santander Scholarships Tech | Reskilling in Data Analytics - Ubiqum Code Academy are designed for people with no experience, so even total beginners can get onto the tech ladder.
Due to the high demand and low supply of analysts, jobs in data offer good average salaries. Meanwhile, for those willing to expand their knowledge, there is a clear trajectory to becoming a data engineer, scientist, or architect. We’ll now go on to explore what data-based jobs are out there at the moment and the ones that are likely to appear in the future.
Companies now heavily rely on data-driven decisions. Data analysts make sense out of massive amounts of data and push companies forward with their insights. It is also beneficial to be able to see things that may seem counterintuitive at first. As the data gets passed on to the data engineer or scientist, it goes from raw data into predictive models using machine learning. This is essential in the insurance, finance, and banking industries.
Amazon is one company that has really capitalised on the potential of data to grow as a business. One easily visible example of this is the recommendation section that appears at the bottom of the screen. In basic terms, this tool analyzes data from similar profiles to suggest related products.
But Amazon’s business intelligence analysts go far beyond recommendations. To keep up with their delivery promises, Amazon mines and analyses data to create machine learning algorithms that can predict products people are likely to buy, as well as the predicted date of the purchase. Therefore, they can stock up their local warehouses with products they know they’re going to sell.
The fact is, there are few companies out there who can deal with such volume in such a short amount of time. Their machine learning engineers play a big role in making Amazon the enormous commercial player it is today. However, this is but one example –now, jobs in data science are diversifying far beyond e-commerce.
Data scientists are beginning to use sensors in all kinds of areas to track data from a multitude of sources. One of the most well-known uses is in sports. In a field where performance is everything, data analyst jobs are popping up all over the place. This provides data-driven decision-making in what was once seen as an area that partially relied on luck.
For instance, in football, teams are turning to sports wearables to track up to 1000 data points per second. This amount of data takes a lot of the guesswork out of tactical decisions and teams are already using it as part of their match preparation. Managers can see weaknesses in their opponents and exploit those weaknesses, leading to some surprising results.
Part of the magic in sports is that element of unpredictability; certainly, it’s difficult to imagine a time when you could be fully in control of a game. However, with big data and cloud computing, it is becoming far easier to use the tools available to control the outcome. Those with the best team of data analysts working for them are sure to have a significant advantage as we move forward into the future of sport.
Some years ago, a well-known architect, Carlo Ratti, made a dramatic career change: he became a data architect. His work focuses on using sensors to make smart cities. With researchers at the MIT Senseable City Lab, Ratti has generated a countless number of impressive projects. These designs explore real-life scenarios that could improve our daily lives.
For example, the Light Traffic project uses sensors and the Internet of Things (IoT) to such an extent that traffic lights are no longer needed. By exploiting data science to facilitate complete awareness of every car’s surroundings, they can all cross an intersection at the same time, seamlessly passing each other with no accidents. Here is a video simulation of how this works on the Senseable City Lab website.
“Many students went to work in different places, from startups to big consultancy companies –the list goes on”.Ariadna Fernández
This kind of project demonstrates the huge variety of jobs in data. Certainly, some of the more complex jobs require advanced degrees and years of experience, but getting started in the industry is a great first step.
It is very difficult to predict how the job market will look in the future. For instance, what would our grandparents have thought if they were told that ‘data engineer’ was one of the future’s most lucrative career paths? It’s an entirely new job based on coding languages that didn’t exist before and things are developing faster than ever.
However, one thing that’s for sure is that having a strong skill set in data will provide a lot of job security for years to come. Techniques and best practices may change, but with a supportive community and open-source materials, it is relatively easy to adapt to movements in the industry.
For now, we can see that as many jobs are disappearing, the data sector is rapidly growing. By reskilling as a data engineer or analyst, you can merge your passion with a fulfilling, prosperous, and stable career path.
Do you want to diversify your career opportunities? The Santander Scholarships Tech | Reskilling in Data Analytics - Ubiqum Code Academy help candidates orient their skillset towards the most in-demand applications. With a six-week course introduction to data analytics taught in either English or Spanish, you can learn more about one of the professions of the future.
(At the moment the Becas Santander Tech | Reskilling in Data Analytics - Ubiqum Code Academy has reached its end, but we encourage you to take a look at the Santander Scholarships to find the training that best suits you and give a boost to your professional career. Seize the chance to develop your knowledge and skills!)
Ariadna Fernández, Data Engineer at Hosco