Coming from a math background, Rokt software engineer Sijia Chen has been able to bring with her a new way of thinking when it comes to tackling problems.
It’s a skill set that has proven valuable for those around her, whether that be through abstracting a bleed simulation task into a probability problem or providing a mathematical proof for the simulation result.
By applying her logical thinking approach, Chen has been able to find the root cause of some unusual behaviours in data. Sometimes, by digging into the data, she is capable of locating
some upstream bugs that violate the business logic without even looking at the code.
Starting last year as a data analyst, Chen transferred to the optimisation team and continued as a machine learning engineer around the mid of the year, after showing a keen interest in of machine learning algorithms, advanced mathematics and statistics.
She made the transition seamlessly and built a completely new LightGBM model for the company’s new market.
As well as her efforts for the company, Chen has also been equally active in the community.
She represented her company at the UNSW career fair, where she encouraged girls to pursue a career in the engineering field. She also helped her company host a Women Hack event.
In the event, as a lot of women were looking for a way to become a machine learning engineer, she explained what machine learning engineers normally do and how to become a machine learning engineer based on her experience.
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