Startup Wisdom, Google Cloud and EDAs

What I learned at Wequity and why you can learn from it too.

End of September I joined Wequity, a digital start-up active in the ESG space as a Data Engineer. Through their products, they want to make it easier for actors in the financial sector to allocate their money in a sustainable manner.

Curious about the main takeaways from this experience ? Then keep reading !

Currently in my last year of Mathematical Engineering KU Leuven and (hopefully) about to finish, existential questions about what I want to be doing next year are never far away. Curiosity around life in a startup combined with the fact that Wequity’s mission - enabling investors to create a positive impact with their money - is something I also care deeply about made for an extremely interesting few job at Wequity consisted of helping the engineering team with the development of their ESG Insights API. Through this tool, the user is able to monitor ESG performance of companies in near real-time based on news and social media data sources.

Part of the Wequity team in our Brussels office (Start it @KBC)

Another very important skill that is part of startup wisdom is what I call ‘the art of the pivot’. Due to limited resources a team is forced to continuously evaluate what is essential and what is not. Determining what are the optimal short-term priorities to reach an -also continuously changing- long term goal is a real craft in and of itself and one that is essential to a startup but also to any organization or project in general.

Exploring the Google Clouds

At Wequity, my days mainly consisted of computer programming. The tasks were very diverse, ranging from integrating a new data source into the pipeline to conducting an investigation into what settings we should use on a certain part of the project to get the best results. Some of the frameworks used were Google BigQuery, Python, Google Cloud Functions, Google Cloud Source Repositories, Github Actions, SQL, Docker, pytest, various scraping libraries, Google Data Studio, Jupyter Notebook,… All of this to illustrate the point that during the internship I had to constantly adapt to a new tool. This forced me to really think about what I was trying to accomplish and if I was using the right means to get to the end of achieving a given task. This was very different from the academic setting I’m used to where you’re often told to use one or the other tool.I also really appreciated that when determining the next target, my personal interest were really taken into account so I could learn about what I found exciting at any given moment.

EDA for Dummies

As you probably know if you’re familiar with computer programming, most tasks are quite straightforward. ‘This should work like this’, ‘if this happens then this’, etc. However, something I realized while constructing an EDA (Exploratory Data Analysis) is that when there is no way to describe the expected outcome of the task, the way in which you structure your work becomes critically important. When doing something ‘exploratory’ like an EDA there is per definition no way to describe the outcome. Moreover this is very seldom the case in real life situations. Structuring your work helps to build trust in your solution by being able to illustrate your methodology and which assumptions you had to make at what point to get to the answer. I have really come to appreciate this way of working over the past few weeks.

These were a few lessons I learned while interning as an engineer at Wequity. During this internship it felt like I was learning a new skill every day, and that’s probably not even far from the truth. Not only did I become a better programmer, but probably also a more structured communicator and a more self-guided professional overall. I am sure the lessons learned will stay with me for the remainder of my career and very grateful for the opportunity.I hope that you also will have learned something through this article and I want to thank you for your interest.

About Wequity

We specialize in providing ESG solutions, aimed at helping clients unlock the power of ESG data through AI-driven screening and reporting solutions.

As the world grapples with the existential problems posed by climate change, Wequity is dedicated to helping the financial industry implement sustainability at the core of its practices. The lack of data availability and the ensuing greenwashing practices that have emerged have complicated this transition, which is where Wequity comes in. By providing unique opportunities to support responsible investing and take ownership of sustainability efforts, Wequity is helping to create a more sustainable future.

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