Shawn Ma
About Shawn Ma
Shawn Ma is the Director of Application Development at Trellance, where he focuses on transforming large datasets into actionable insights. He has over 26 years of experience at Nielsen, where he held various roles and contributed to optimizing products and services in retail and consumer intelligence data.
Current Role at Trellance
Shawn Ma serves as the Director of Application Development at Trellance, a position he has held since 2021. In this role, he focuses on transforming and analyzing large datasets to derive actionable insights. He is passionate about member-centric data integration and predictive analytics, which are critical components of his current responsibilities. His work involves developing modern financial data platforms tailored specifically for credit unions and community banks.
Previous Experience at Nielsen
Shawn Ma has a substantial history with Nielsen, where he spent 26 years in various roles. He began as a Project Manager and Principal Software Engineer from 2000 to 2003. He then served as Acting Director of Data Management from 2003 to 2007, followed by a role as Program Manager for Global Data Integration from 2007 to 2014. From 2014 to 2018, he worked as Program Manager for Data Acquisition, and most recently, he was a Tech Lead in Retail Intelligence Data Engineering from 2018 to 2021. Throughout his tenure, he was instrumental in optimizing products and services for retail and consumer intelligence data.
Education and Expertise
Shawn Ma holds a Master's degree in Engineering Science from the University of South Florida. His educational background provides a strong foundation for his expertise in data engineering. He has developed a deep understanding of building high-performing teams and has a strong focus on member-centric data integration and predictive analytics, which are essential in his current and previous roles.
Professional Focus and Skills
Shawn Ma has a strong focus on transforming and analyzing large datasets to derive actionable insights. His expertise includes building high-performing teams in the data engineering field. He is skilled in optimizing data integration processes and has a background in predictive analytics, which enhances his ability to manage complex data projects effectively.