Markets Media spoke with Cindy Yeung, Data Analyst, Liquidnet, who won Rising Star at the 2025 Women in Finance Asia Awards.

What does this award mean to you, and how do you see it influencing your path going forward?

The award is incredibly meaningful to me because it validates the effort and passion I have put into my career, especially being recognized together with so many talented leaders and changemakers in the Finance industry. I am also grateful to be part of this transformative movement in celebrating more and more the contributions and successes of women in the industry.  While I am proud of this milestone, I would like to treat it as a stepping stone – this recognition motivates me to continue pushing boundaries, taking on new challenges, and contributing to innovative solutions in finance.

What excites you most about the role data plays in shaping trading strategies and decision-making today?

What is most exciting is how data has shifted the industry to adopt more precision-driven decisions. The changes include broader access to alternative data, enhanced scenario simulation on trading strategies and millisecond latency on terabytes of data

With the right analytics, we can act smarter, uncover patterns, mitigate risks and seize new opportunities which were less visible a couple of years ago. The ability to process newer real-time data and adjust decisions instantaneously and proactively – especially in such fast-paced finance markets – feels like working at the frontier. At the same time, this intelligence keeps expanding exponentially – it is all about anticipating tomorrow’s unknowns.

What kinds of projects or insights have you worked on that you feel have made a tangible difference for traders or clients?

While there is tons of research around the APAC lit market, our  analytics team at Liquidnet runs projects to deep dive into the APAC dark and block market landscape to uncover hidden liquidity. Unlike lit markets, dark trades lack transparency with limited public data however an increasingly significant portion of trading activities occur in the dark in APAC. With new dark venues launching in exchanges (e.g. Korea and New Zealand), it is a continual structural shift. Our reports compile fragmented data sources and aim to help the buy-side understand dark market structure and navigate trends.

What have you found most challenging—and most rewarding—about working in a fast-paced fintech environment?

I believe the most challenging element is to stay ahead of changes. With sheer volume and lability of data, how to extract the real, meaningful insights before they become obsolete is a big question. Also, with the advancement on new fintech, it is important to adapt and bridge the divide between finance experts and tech-native teams.

Two sides of the same coin – the things that make fintech demanding also make it exhilarating. I feel rewarded when seeing ideas scale fast and turning those challenges successfully into impact. Furthermore, the fast-paced environment allows me to learn continuously, open new doors and venture into a new domains outside my role.

Data analysis requires a blend of technical skills and business intuition. How do you balance the two when extracting value from complex datasets?

Four key principals help me balance between technical skills and business intuition. First, I dedicate time to upskill technical knowledge from both internal colleagues and external courses. Nowadays, people are open to sharing and a lot of free resources are available online. Second, always start small and then scale. It is easier to achieve targets when breaking them down into small goals and learn from mistakes. Aiming too high at the beginning can lead to failure quickly. Third, be proactive to communicate more and always stay curious to dig deeper. This helps clarify business concepts and align with stakeholders’ needs. Finally, stay humble and listen to feedback. I find it useful to share interim results with business teams early for their suggestions and comments. It can facilitate the data analysis going into desired direction.

What advice would you give to other women interested in building a career at the intersection of data science and finance?

From a basic standpoint, it is important to own technical expertise and master the fundamentals on both Finance and Data Science. Then keep learning to go beyond the basics. These approaches can help build up your strength and portfolio.

This field may not be easy, but the upside is limitless. Take courage, be heard and let your work speak for itself. Most importantly, always believe in yourself – your unique perspective can drive innovation.  The Finance industry needs more women who can build data models, understand the business and thrive and contribute to this ever evolving industry!