Finding the Beauty in STEM

Finding the Beauty in STEM

Studies by groups motivated to understand the mindsets driving our STEM industries, like the Organisation for Economic Co-operation and Development, have found deeply ingrained attitudes that STEM is predominantly a man’s space. It’s this status quo that Koh Hui Lin and Sarah Gui, two of the many women in STEM at Sephora Asia, want to shift. Today we’re hearing firsthand how women don’t just belong to STEM – they’re thriving in it too. 

 

Hey there ladies! Could you introduce yourselves? 

Hui Lin: Hi, I’m Hui Lin! I’m a Software Engineer sales engineer at Sephora S.E Asia. I joined the team in 2022, and right now I work out of Singapore with a team of 10 diverse and passionate people. 

Sarah: Hello, I’m Sarah! I joined Sephora in 2022 as a Product Data Analyst, in charge of data analytics for the Product team.

 

What’s an average day for you at work? 

Hui Lin: Well, to dive a little deeper in my role, I’m a fullstack developer dealing with the sales/purchase engine for Sephora Asia’s e-commerce site. That means I work with software that handles customer orders, refunds, returns, vouchers, and more. As you might expect, I spend a lot of my job behind a computer and studying codes (laughs), but a significant part is also spent collaborating with my team and all the other teams that make the Sephora ecommerce run smoothy. 

Sarah: As a Product Data Analyst, I analyse data to identify user patterns and gaps in our marketing funnel. It’s my job to tap on this data to come up with improvements and new ideas to enhance our ecommerce or web experience. I collaborate with the many teams within the whole company to make those improvements and ideas a reality. Like different pieces of the puzzle but all the user sees is the whole picture.  

 

Are there any misconceptions people have of you and your job?

Hui Lin: Well yes! I think many people think that buying something online is pretty straightforward. Afterall, it’s just ‘add to cart,’ ‘checkout,’ and ‘pay’ before the user gets their products delivered to their doorstep, right? A lot of work actually goes on behind the scenes to make your user experience a smooth one. As people browse, redeem points, and buy products on the site, they don’t realise it’s a whole ecosystem of working together on different segments like the UX/UI, reward redemption, member tiering etc. 

Sarah: I agree, when people buy a product, so much thought has been put into making the buying process feel effortless and personalised – and shopping should be like that! When people hear my work has to do with user and product data, they assume it’s as simple as Googling a keyword, or generating reports based on customer surveys. Big data is more complicated than that – we need the technical skills to crunch through all that data, the soft skills to deduce patterns, and the critical thinking to suggest improvements based on that. For example, if we identify a user pattern where two product categories are often checked out together, we may tweak our product suggestion algorithm to recommend these categories to each other more often. 

 

What do you love about your job? 

Hui Lin: As the different teams within our company discover new strategies to improve our ecommerce site, I love the variety of problems and autonomy we have to collaborate, innovate, and execute solutions across teams. For instance, the product data analytics team wants to identify users’ browsing patterns to provide better user experience through more relevant product recommendations, or perhaps the business team identifies the need to experiment on a call-to-action button on the product page – we’ll brainstorm together on how best to implement that. It’s Sephora’s style to provide us the freedom and flexibility to deliver the most satisfactory outcome to serve our customers.

Sarah: I really appreciate the environment in Sephora – there’s a pretty flat hierarchy and a start-up culture vibe that makes collaboration and ideation very inclusive and easy. What I love about product analytics is that you never know what you are going to get from the data as there are so many different user profiles and insights to dig into. I also love the data driven approach Sephora has where most product features we develop come from what the data is telling us.

 

How do you think Sephora Asia has helped promote a diverse and inclusive workspace? 

Hui Lin: The female representation and diversified culture at Sephora makes Sephora a “safe space” for me. I don’t worry about being passed over for promotion based on my gender, or being seen as less professional compared to my male colleagues because I don’t dress in a suit and tie. Also, having diverse personal and/or working backgrounds make us fundamentally different when it comes to thinking about an issue/solution, or even just what it means to bea team, in the workplace setting. It means we work out of our comfort zone a lot of the time, and yes, misunderstandings come up that need to be worked through sometimes. But it also means a much more meaningful workplace where we get to broaden our horizons and minds everyday.

Sarah: I love how Sephora continuously upskills us, so we all have fair and equal opportunities to advance our careers and skill sets. For instance, we took part in a Deepracer League, in 2022 co-hosted by Amazon Web Services, where we used coding, human and machine learning to create algorithms to remotely control toy cars to complete a mini race course! It was a really fun way to pick up new skills in machine learning (ML), Python programming, and coding, especially for our non-tech colleagues. I even helped code the algorithm that produced the winning team despite being quite new to ML! (laughs).

 

How is STEM transforming the beauty industry? 

Sarah: I thin technologies like ML and artificial inelligence could create a more personalised beauty experience for customers. This goes beyond the moment they enter Sephora stores – physical or online – to the moment they encounter marketing materials or engage with customer service. We can anticipate their likes, needs, and behaviour to make beauty more accessible and enjoyable for them. 

Hui Lin: Technology has allowed the beauty industry to make the leap from brick-and-mortar to the digital realm, making it more accessible and personalised. Even today, data-driven approaches to beauty mean users have an entire catalogue at their fingertips, complete with tailored recommendations, without having to leave the house. Just like Sarah mentioned, I think M and AI could massively advance those aspects and more for beauty providers like Sephora. Let alone generative AI…

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