With a passion for data and analytics, Catalina Herrera has spent her entire career helping the industry push beyond digitalization to business transformation. Currently, she works as a Principal Solutions Engineer at Dataiku.
Catalina has held educational and technical positions, worked with state-of-the-art technology solutions across multiple industry verticals, and served as a data scientist and advanced analytics consultant.
Especially for the WomenTech Network, Catalina agreed to give an interview and share her story.
Join the Women in Tech Global Conference 2022 to hear Catalina's talk "The Power of Collaboration Within the Data Science Pipeline", and other inspiring sessions.
Are you excited to be among the speakers at the Women in Tech Global Conference 2022 and what motivated you to join our community of 100 000 women in tech, minorities, and allies?
Yes! Inspiring more young women to pursue careers in science starts with simply sharing our stories. We empower new generations to write their own history, and I find that very rewarding both professionally and personally.
I am also passionate about data and what we can do with it with AI and ML, and I see this conference as a great opportunity to learn from other participants, hearing inspiring real-life stories based on years of experience that these women bring from around the world.
It is also a great opportunity to share my own experience and lessons learned after over 15 years of being immersed in this business and building out AI/ML use cases. Solving business problems across the globe in some of the world's largest companies across many verticals puts me in a unique position to add value to this conference.
Share with us about your background, your journey in tech, and what inspired you to develop your career in this direction?
I studied electronic engineering, and after college, I became an electronic engineer at Texas Instruments. Once I got into that role, I really began to realize the importance of data. So, I guess you could say I didn’t plan on making this my career, but I realized that I had a strong acumen for understanding data at a deep technical level as well as at the business level. This unique combination of skills allowed me to move into the software business and help other organizations make sense of their data. Every industry needs to analyze and maintain its data, and professionals are needed to help ensure data is being managed and used properly.
During my role at Texas Instruments, I was part of the Yield Team. We had to be very efficient to make sure that we would get optimal yield as a result of the semiconductor process. This was a big problem to solve, with each process being more than 10,000 steps, millions of data rows per day, across multiple silos to analyze. The most important part of making this work was being proactive. The sooner we were able to identify potential yield issues, the more savings we could generate. We were able to successfully implement predictive analytics techniques that impacted KPIs, thus optimizing the Yield flow and minimizing unnecessary expenses. We ended up helping TI realize millions of dollars in value because of projects like this.
Since then, I have been exposing my customers and my community to the "art of what's possible” when your business is properly represented with data. In 2020, my influence in the AI community in Texas resulted in being recognized as one of the top 30 women in Artificial Intelligence Advancement.
Who would you advise to attend the Women in Tech Global Conference and why?
Everyone that is passionate about what technology brings to the business should find at least a couple of the conference sessions very interesting. Women will also have the opportunity to be a part of a community of more than 100k+ passionate individuals, each resonating with their own history, experience, and insight.
🎤 In her #WTGC2022 session "The Power of Collaboration Within the Data Science Pipeline", Catalina Herrera will highlight some of the key things you have to consider when developing a data strategy, explaining key concepts like Responsible AI, AI Governance, and technology resilience.
