Articles by Caitlin Hudon
- Imposter Syndrome in Data Science
Imposter syndrome is common in data science due to it being a new, interdisciplinary field that is constantly evolving. Data scientists come from varied backgrounds and cannot be experts in all aspects. Caitlin deals with imposter syndrome by accepting she cannot learn everything and knowing her unique experiences and skills. She advocates normalizing saying "I don't know" and encourages sharing what one is learning. To help others, the community should embrace questions, transparency about learning, and understanding that all data scientists are continuously developing their skills.