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Blog / Culture
Newly-fledged Ravelin Software Engineer, Gonza Ferreiro Volpi, discusses his big move from data science to engineering, why he made the transition & how others can do the same.
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“One of the best things about data science is that it’s a welcoming field. Data as we know it today is a relatively new thing and most companies have more data than they know what to do with. So demand for data people is high. Companies are always on the lookout for people with different types of backgrounds.
“When I was in college, being a data scientist wasn’t really a thing. I studied both Business and Computer Science, but then I ended up in Marketing. That was the field to be in if you wanted to understand user behavior through data (or so I thought!).
“As data became more accessible and valuable, I found myself moving closer to that area. I realized I was happiest working behind a computer doing analysis and looking for insights that I could pass on to my team. That’s when I decided to officially pivot.
“I moved to London from Uruguay to do an immersive program with General Assembly. I was lucky enough to find Ravelin right after I finished the program.”
“There are so many different data scientists out there. Some roles will focus on machine learning, so there’ll be more emphasis on mathematics and statistics. Others might have a stronger focus on data analysis, dashboarding and solving business problems.
“On top of this, there's the computer science side of things. Programming is a key component in the day to day life of any data scientist. Cloud computing also means we work with tools like Docker and Kubernetes. So a strong understanding of software engineering is also valuable.
“An all-round data scientist is kind of a unicorn. It’s rare to find someone with a strong background in all these disciplines. The skills you need will depend on the path you might want to take.
“Ravelin is great because they understand that data science isn’t just about programming and mathematics. It’s also about understanding business challenges and clients.”
“I’ve always been interested in computer science. When I got into data science and got to grips with Python, I remembered how much I enjoyed programming.
“Having said that, Software Engineering is much more than just programming. I recently came across a definition of Software Engineering that I love – “programming over time”. In other words, it’s the production of code and infrastructure that is sustainable and scalable over time.
“This approach is a real shift for me and I am excited to learn more.”
“There’s definitely some overlap and transferable skills between both fields. I feel like there’s a clear sweet spot in the middle. We’re still asking ourselves – what does the data tell us about our own clients and their usage of our product? And, how can we use this data to diagnose bugs and improve our code base?”
“It’s not an uncommon move, but it’s not typical either. Despite the overlap, there’s still a big gap between both fields.
“I think any data scientist can benefit from understanding software engineering. But that doesn't mean they need to make a full transition. Making the move to engineering can often be a step down for data scientists. Also, sometimes the knowledge gap is just too wide, which can make it a painful transition for the employer and the employee.
“Finding a company like Ravelin who are willing to bet on someone senior moving into a new field is rare."
“I’m a big fan of slide decks for presenting ideas and projects. And coming from data, I’m all about storytelling. I often find that putting together the narrative helps me clarify my own thoughts. I was able to show my manager the full journey – how I got to this point in my career and where it could go.
“It wasn’t an easy conversation, but having the slide deck helped me out. I knew what I wanted to do and I had a plan – it was just a matter of saying it out loud. I also came up with a transition strategy, so it wouldn’t be a painful experience for anyone. Needless to say the meeting went well!
“My manager Ruth has a gift with people and she’s been the most empathic boss I’ve ever had. Once I got her on board, I knew I could trust her to take my proposal forward to the relevant people.
“That said, it took time. Over several weeks they reviewed my plan and reached out to other members of the team. It was reassuring to know that my proposal had been thoroughly evaluated. It meant they believed that I could do this and succeed.”
“I am working with the Payments Fraud team. We are responsible for building and maintaining Ravelin's real time data processing capabilities. We keep clients informed on the profile of millions of transactions a day. That could be, for example, information on the customer, payment method, location or whether the transaction was successful or not. We also share the impact that our recommendations have on performance.”
“I had just over four months to learn the programming language, Golang. That was the biggest hurdle, so I got my teeth into that first. Now that I’ve crossed that bridge, I’ve been focusing on getting used to the tools we use at Ravelin. I’ve also been consolidating my knowledge of the fundamentals of software engineering – concepts like testing, documentation, architecture patterns, etc.”
“I have three things. One, really think about what you want. Don’t expect people to tell you the what, how or when. Being proactive is key!
“Two, try to think of alternatives that are not only beneficial for you, but also for the company. Why should they choose you over a new hire with experience? How will the company benefit? What does the transition process look like?
“Three, be patient, be decisive and embrace impostor syndrome!”
Lola Omo-Ikerodah, Content Writer
Blog / Fraud Analytics
Fraud prevention is a delicate balance between stopping fraud and maintaining good customer experiences. But what is the most effective way to measure this outcome?
Ravelin Technology, Writer
Blog / Machine Learning
Online payment fraud is one of the biggest threats facing grocery merchants. And it’s only gotten worse. How are fraudsters using the cost of living crisis to take advantage of your business?
There’s a new fraud threat on the rise – and it’s your customers. First-party fraud is infamously tricky to catch and a huge revenue risk. How can you detect and deter criminal behavior in your customer base?