What is “truth” anyway? The impact of bias and inadequate ML model validation and what to do about it.
Continuing our 5-part webinar series on the, "Top 5 Pitfalls to Avoid When Developing Your Data Science Team," we are thrilled to interview Randi Ludwig of Dell Technologies and Amarita Natt of Econ One as our panelists.
We will discuss how data science and engineering teams are affected by insufficient validation of models and methodology. This 45 minute webinar will cover topics including:
- The importance of the methodological approach for data science within organizations
- How to structure teams and design processes to reduce bias
- Quality control measures organizations can deploy to avoid meaningless/incorrect models
- What role on data science teams is best suited to ensure model quality?
Randi R. Ludwig
Data Scientist at Dell Technologies
Randi R. Ludwig is a Data Scientist at Dell Technologies within Support and Deployment Services. She brings data science solutions to business problems involving tech support, warranties, and repairs on Dell products. She also focuses on raising visibility for data science at the executive level and connecting global Dell data scientists into a networked community that can collaborate and learn from one another. Additionally, she is a co-organizer of Women in Data Science ATX and promotes diversity and fostering a welcoming space for newcomers to the field. Before venturing into industry, Randi completed a PhD in Astrophysics at UT Austin, including research on both active galactic nuclei and how students learn astronomy, which gave her experience with varied statistical data-mining techniques and many kinds of data sets.
Managing Director at Econ One Research, Inc.
Amarita Natt is Managing Director at Econ One Research, Inc. in Los Angeles, CA. Dr. Natt performs empirical data analysis on large datasets to assist clients in determining outstanding liabilities for financial reporting.
Most recently, Dr. Natt has performed analysis in the airline industry, creating models to predict frequent flier user behavior and assess the impact of proposed changes to loyalty programs or airline routes. Her prior work has included creating and implementing analytical models to forecast future headcount and compensation reserves and developing methodologies to analyze the value of embedded software in client inventory. Dr. Natt has worked with clients in various industries including media and entertainment, medical devices, technology, and retail, and has extensive experience working with large transactional datasets.
In addition to consulting, Dr. Natt has taught microeconomics at Northeastern University and she designed and teaches a seminar course titled “Data Science for Social Scientists” for the UCLA Department of Sociology.
Invite your team!
Who else would benefit from learning about the topics of this webinar?
We'd love for you to invite them! As a reminder, the Webinar is on April 11, 2019 at 2 pm EST.