Applications of Data Science
How do we effectively integrate and utilize data science in mature engineering and business systems? Connie talks about her experience in how this can be done, drawing from both experiences in Big Tech and leading the data efforts at an early-stage tech startup.
Take-aways
In this episode
Connie Yang
Lead Data Scientist, Pallet
At Pallet, Connie has been leading various data science work streams on integrating machine learning, intelligence, and automation into the entire Pallet product--including creating multi-label, multi-class auto labeling machine learning models deployed as cloud-native APIs to be integrated into Pallet backend, creating holistic and diagnosable health scores for various stakeholders and scaling out Pallet's data collection system.
Demetrios Brinkmann
Host
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.