Walter Shields Data Academy

Building a Successful Career in Data Science: Tips from an Industry Insider

The demand for data scientists in the finance sector is on the rise, with several companies investing heavily to recruit the best. However, a crucial issue that affects the quality of talent in data science is a lack of fundamental knowledge. This is a point raised by Marco Jean Aboav, co-founder of indexing infrastructure fintech Etna Research, who has released a comprehensive guide for data scientists. In this post, we will delve deeper into why fundamental data science knowledge is key in finance roles.

Aboav states that candidates with fundamental knowledge account for less than 5% of applicants. As the industry moves towards hard skill data science, he emphasizes the need for data scientists to become more like developers than just scripting guys. Unfortunately, many data scientists tend to showcase advanced techniques without demonstrating any core knowledge. This trend results in a shortage of qualified data scientists in the market.

To be successful in a data science role, you need to think like a computer scientist. In the US quantitative finance industry, a tendency to recruit individuals from finance or economics backgrounds often exists. However, Aboav suggests that companies should hire someone who is proficient in the basics and provide ad-hoc training to get the best out of that person.

It is essential to note that possessing fundamental data science knowledge goes beyond mastering programming languages like Python or R. To succeed in a data science role, you must understand the mathematical fundamentals that underlie the techniques you apply. For example, you should have a solid grasp of statistics, data modeling, and data structure. If you lack these fundamental skills, then you won’t be able to apply advanced techniques effectively.

Moreover, as the competition in the finance sector increases, it is no longer enough to just have an MBA, finance, or economics degree. Employers in the industry want to hire individuals who have highly specialized technical skills they can apply in the field. Having a degree in computer science, statistics, or mathematics positions you as a top candidate in data science roles.

The finance industry is incredibly fast-paced, and the competition is intense. Employers are seeking individuals who are well-equipped with fundamental data science knowledge because it is key to solving real-world problems in finance. For data scientists to remain relevant in the industry and progress in their careers, it is essential to invest time and effort in building foundational skills. By doing so, data scientists will be better positioned to surpass expectations and significantly contribute to the industry.

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