People Analytics at Pinterest | Trevor Fry | Data Science Hangout

To join future data science hangouts, add it to your calendar here: https://pos.it/dsh - All are welcome! We'd love to see you! We were recently joined by Trevor Fry, Lead Data Analyst at Pinterest, to chat about people analytics, bridging the data science practice gap, the future of the field including AI, and measuring the value of data teams. We also celebrated a birthday 🎉 In this Hangout, we explore bridging the data science practice gap—the challenge of effectively translating research findings and data insights back to business leaders and stakeholders. Trevor discusses how the nature of people data is particularly sensitive, requiring careful handling, and emphasizes the importance of adapting your communication and language to your specific audience. He also shares insights into the future of people analytics, especially the potential of AI and LLMs for analyzing unstructured data like survey comments, while noting the challenges of ensuring reliability for scientific applications. Trevor also touched upon the difficulty of measuring the return on investment (ROI) for people analytics functions and discussed common analytical methods used in the field, such as Structural Equation Modeling (SEM) and relative weight analysis (RWA). Resources mentioned in the video and zoom chat: 🔗 Storytelling with Data by Cole Nussbaumer Knaflic → https://www.storytellingwithdata.com/ 🔗 Society of Industrial Organizational Psychology (SIOP) → https://www.siop.org/events/the-annual-conference/ 🔗 Relative Weight Analysis (RWA) R package → https://martinctc.github.io/rwa/ 🔗 People Analytics: Regression Modeling by Keith McNulty → https://peopleanalytics-regression-book.org/ 🔗 Structural Equation Modeling (SEM) info → https://stats.oarc.ucla.edu/r/seminars/rsem/ 🔗 Ollama (local LLMs) → https://ollama.com/ 🔗 Posit blog: Secure AI-Assisted data science in R with Posit and Snowflake → https://posit.co/blog/ai-assisted-ai-posit-snowflake-cortex/ 🔗 TidyTuesday GitHub repo → https://github.com/rfordatascience/tidytuesday 🔗 TidyTuesday in Python GitHub repo → https://github.com/posit-dev/python-tidytuesday 🔗 Forecasting: Principles and Practice (Python version) → https://otexts.com/fpp3/ (R version also mentioned) 🔗 Causal Inference: The Mixtape by Scott Cunningham → https://mixtape.scunning.com/ 🔗 Text Analysis using Quanteda (R package) YouTube video → https://www.youtube.com/watch?v=tf5FmXiwEQE If you didn’t join live, one great discussion you missed from the zoom chat was about the definition of a "data scientist" and whether individuals feel like they are "really" data scientists, highlighting the varied backgrounds and nonlinear paths in the field. If you have any imposter syndrome around data work, you're not alone! ► Subscribe to Our Channel Here: https://bit.ly/2TzgcOu Follow Us Here: Website: https://www.posit.co Hangout: https://pos.it/dsh LinkedIn: https://www.linkedin.com/company/posit-software Bluesky: https://bsky.app/profile/posit.co Thanks for hanging out with us! 💛