The Next Generation: The Story of a Data Science Apprentice at DataLab
For the past six months, I have been working as an intern at Serasa Experian DataLab. My internship was part of the Apprentice program designed by the Brazilian government to help young people enter the job market. By law, medium and big size companies are obliged to hire a number of Apprentices equivalent to roughly 10% of employees performing jobs that require post-secondary education. The Apprentice program is exclusive for people of ages between 14 and 24 who are enrolled in or have finished High School but are not in university. Paired with the work they do at companies, apprentices are required to attend classes six times per month. Those classes are supposed to teach real-world skills and the intricacies of the job market.
I applied for a job at Serasa Experian through the Apprentice program. I had seen an ad to this job opening in a website that published trans-friendly job openings. At first, my main drive to apply was the money I needed for medical purposes. My view of a job was pretty much selling my workforce, getting a salary, going home, trash-talking my bosses behind their backs, that sort of thing. I was expecting to get a boring job, be stuck in a desk and get to the point of hating myself and my work. But I was wrong. Upon being hired, I was informed that I would be working at Serasa Experian’s DataLab, a place described to me as a very cool place, responsible for driving innovation and data research for Experian in all Latin America.
I was very scared about working at DataLab. I imagined it to be a very oppressive place. I thought that it would have no windows, that it would look pretty much like a basement with low celling, that it would be a place where I would be seen as nothing and would be looked down upon. I did feel lucky about going to the “biggest data lab in Latin America” but I had a legitimate fear of the unknown. Fortunately, I was very wrong. The DataLab was not paradise, but it was close enough, it looked like one of those high-tech companies we see on TV. But then, I had new fears.
This time my fears were focused more on my presence in the Lab. I was to be the first Apprentice ever in Serasa Experian’s DataLab and would work in a completely different place of all the other Apprentices I had befriended with during the hiring process. I was all alone. And not only that, but I also had to live up to the expectations people would have about me. But again, I quickly learned that there were, in fact, no expectations towards me. People there were more concerned that I learned things, and not necessarily with the things I already knew. In fact, I was very encouraged to say whenever I didn’t understand something or thought anything was not clear. That was freeing, but also weird. I had just finished my high school career, so my experience was that I had to be the best at everything, and that meant knowing all the answers to every question, but now I was free to not knowing things.
Because of that freedom, I was prompted to learn the most important thing I learned here. I had a hard time to know what I knew and what I didn’t. In school, knowing things was almost the same as memorizing textbooks or repeating the steps given by my teachers, but at DataLab, knowing things meant actually understanding them and how they could be applied to the specific situations we were presented with. I think that this was the best lesson I got out of this whole experience, that knowing things is important, but knowing when you don’t know things is also important. I learned that there is nothing wrong with not knowing something and one should make it clear when one doesn’t understand things, that is what makes people smart and efficient.
However, even with this realization, it was still easy to feel small working at DataLab. There was this unspoken tension between the younger generation and the older one and I didn’t quite fit in either of those groups. Because the young people working here were so smart, to the point of challenging their older counterparts, I felt dislocated, because I didn’t think I was smart enough. I did learn that I didn’t need to be the best one there, I didn’t need to be the smartest or the wittiest, I didn’t need to exaggerate my abilities to impress people. If I were there, they were aware of how much I knew and if they thought that was enough, then it was.
Although I was working in DataLab, I still had weekly interactions with the other Apprentices from Serasa Experian because I had to attend classes as a part of my Apprenticeship. Because of that, I could compare my experience with that of the other Apprentices, not only from Serasa but from other companies. We all had been hired to the position of Administrative Apprentice, but we did extremely different things. Most of the other Apprentices had befriended Apprentices and not people of the exact area they worked at. Meanwhile, I had just people from my own area to befriend with. In the end, it was very positive because it allowed me to have deep talks with people that had similar interests to mine, but with more experience. Aside from making friends, I could notice that my experience was different from that of other Apprentices because I was heard in my job. It was hard at first for me to say anything but when I got to express myself, I was heard by the people here at DataLab. Another big difference was the fact that I got to learn academic-related things that will help me in the long run, so I wasn’t stuck just memorizing tasks and praying that my supervisor would not be mad at me out of anywhere.
There was a great concern from my mentor about not only my performance and development inside the work structure but also about how I felt being here. Despite the efforts to become a more inclusive place, the DataLab still suffers from the same diversity issue that other tech companies: it is composed almost entirely of white cis men. Being surrounded by white people was nothing new to me, I had studied all my life in middle-class top-notch schools thanks to the scholarships I got, so I had pretty much lived with white people all around all the time. But the concerns were not only about my well-being regarding my skin color — a concern my mentor probably has because he was in the same position as me — but just a general concern because, during the hiring process, a large portion of my life had been exposed, without my consent, to strangers who would become my work colleagues. Despite his concerns, the people here were very nice and kind, they would always treat me with respect and be very patient with me. My mentor was also concerned about how I felt regarding my work if I were doing things that mentally challenged me, if I enjoyed what I was doing and if I were comfortable doing it. He made it clear to me that I was free to speak up about the tasks he gave me, to question things and to share my thoughts.
Although I could praise the DataLab all day, I find it important to note that it has problems. One of the problems that is easily noted here is that the traditional corporate mentality is not always in agreement with the goals and the structure of the DataLab. Of course, the DataLab isn’t detached from reality, it still has a hierarchy, albeit it is a more flexible one, and it is still part of a company, meaning it cares more about the bottom line than about anything else. Nevertheless, some sectors of the company are more on the traditional side of the spectrum, having a more rigid structure. This discrepancy sometimes resulted in internal conflicts, especially regarding how the Lab should operate.
Aside from the previously discussed abstract personal skills I was able to develop working here, I also learned practical things. For instance, I learned how to live within a corporate environment, how to navigate the battle of egos that pretty much compose the fabric of the internal conflicts in big companies. But I learned how to navigate it from the outside, since, as I previously stated, the DataLab isn’t subject to so much of that traditional company structure. It was a nice thing to learn. In one hand, I have only the experience of a non-traditional environment, with my knowledge of the traditional work environment coming solely from observation and second-hand accounts, which could be prejudicial for me if I ever have to work in a traditional environment. But, on the other hand, I have this knowledge and I know how things could be better, so I could improve my situation in pretty much any place I work. I also believe that forming an opinion as an outsider gives you the chance of analyzing situations from a less biased position. Furthermore, it is very likely that companies will progressively abandon their traditional ways, at least in appearance, to look cooler to the younger generation and further seduce their employees.
Another very practical thing I learned was how to program. When I got to tour Serasa’s main building, I remember telling another Apprentice that I felt I was going to work at ctOS. He laughed and said that Watch_Dogs was a bad game. DataLab doesn’t look like ctOS, not even close. This is not a bad thing per se, maybe it just points towards the inconsistency of the game. Anyway, when I got here, I didn’t know how to program. I mean, I knew HTML because of my school’s program, I knew the general concept of a variable and “if and else”, but I didn’t know how to put this all together to produce something. I learned how to program. Not only learned how to join diffused and vague concepts until something was produced, I actually learned how to program, to understand the algorithm I was implementing and to do something that made sense instead of smashing things together until something happened. If Watch_Dogs were a good game, I would say I’m prepared to be a member of DedSec now.
While working here, I was able to perform tasks that enriched my knowledge and to produce something I am proud of. I am very critical of myself and of everything I do, so to state that I did something that made me proud is a big achievement. I did a notebook about applied K-Means. I know that’s not much, that K-Means is a basic algorithm, but I am so proud of doing it and understanding what I was doing that I don’t care all that much if it looks lame.
There are other aspects of the work environment that I would like to highlight, for example, the gender-neutral bathroom. I was very skeptical about gender-neutral bathrooms because I thought that maybe they were dangerous or uncomfortable. I was wrong. Gender-neutral bathrooms are good and I like them now. There is also the fact that the bosses work in the same space as we do, so we feel more comfortable talking to them. The free food we get if there is an event is also neat. The arcade and pinball machines add a nice touch to the environment, especially when combined with the overall design of the place.
In conclusion, working here has been great, so great in fact that I’m sad about leaving to go to university. I wasn’t prepared to feel sadness over leaving my job but here I am. Both my work and the personal relationships I got in this job are things that I will forever cherish because they helped me grow as an individual and as a worker. DataLab is not what I expected, in some aspects it was better, in others it was worse, but the overall balance is very positive. I wish everyone got the chance to have this kind of rewarding job and it seems to me unfair that most don’t, so I will just consider myself lucky and thank whichever god there is that I got this job.