Meet Catherine Nelson, a geophysicist turned Principal Data Scientist at SAP Concur, discussing her journey and insights into building machine learning pipelines. She emphasizes the importance of data preparation and training, model interpretability for ethical ML, and the value of diverse backgrounds in the field. The podcast also covers topics such as data quality, auditing, and favorite AI-related books.
23:59
forum Ask episode
web_stories AI Snips
view_agenda Chapters
auto_awesome Transcript
info_circle Episode notes
question_answer ANECDOTE
From Rocks to Data
Catherine Nelson's background is in geology and geophysics, where she studied ancient lava flows.
She transitioned to data science after finding limited job opportunities in geology.
question_answer ANECDOTE
Greenland Exploration
Catherine worked for an oil company, which provided travel opportunities like exploring Greenland.
She later left due to ethical concerns about the industry.
question_answer ANECDOTE
LinkedIn's Nudge
While job searching in Seattle, Catherine was bombarded with data science job postings on LinkedIn.
Intrigued, she explored the field and began learning Python and machine learning.
Get the Snipd Podcast app to discover more snips from this episode
Meet Catherine Nelson, Principal Data Scientist at SAP Concur and author of the upcoming O’Reilly book “Software Engineering for Data Scientists”. Join us as we talk about Catherine's amazing career journey as she pivoted from geophysicist to working on setting the standard for building machine learning pipelines. According to Catherine, it all starts with how you prepare and train your data!
Catherine Nelson is a data scientist and author of the upcoming O’Reilly book “Software Engineering for Data Scientists”. She is a Principal Data Scientist at SAP Concur, where she explores innovative ways to deliver production machine learning applications which improve a business traveler’s experience. Her key focus areas range from ML explainability and model analysis to privacy-preserving ML. She is also co-author of the O'Reilly publication “Building Machine Learning Pipelines", and she is an organizer for Seattle PyLadies, supporting women who code in Python. In her previous career as a geophysicist she studied ancient volcanoes and explored for oil in Greenland. Catherine has a PhD in geophysics from Durham University and a Masters of Earth Sciences from Oxford University.