Sheetal Borar
Sheetal Borar is a senior applied scientist at Etsy, where she works on retrieval systems powering large-scale recommender systems. She has spoken at PyData Global and PyData NYC and has several publications under her name and is recognized as a strong advocate for knowledge sharing and community building. She has gained experience across multiple industries and has about five years of professional experience in building machine learning solutions.
Sessions
Recommender systems power everything from e-commerce to media streaming, but most pipelines still rely on collaborative filtering or neural models that focus narrowly on user–item interactions. Large language models (LLMs), by contrast, excel at reasoning across unstructured text, contextual information, and explanations.
This tutorial bridges the two worlds. Participants will build a hybrid recommender system that uses structured embeddings for retrieval and integrates an LLM layer for personalization and natural-language explanations. We’ll also discuss practical engineering constraints: scaling, latency, caching, distillation/quantization, and fairness.
By the end, attendees will leave with a working hybrid recommender they can extend for their own data, along with a playbook for when and how to bring LLMs into recommender workflows responsibly.
AI is transforming data careers. Roles once centered on modeling and feature engineering are evolving into positions that involve building AI products, crafting prompts, and managing workflows shaped by automation and augmentation. In this panel discussion, ambassadors from Women in Data Science (WiDS) share how they have adapted through this shift—turning personal experiments into company practices, navigating uncertainty, and redefining their professional identities. They’ll also discuss how to future-proof your career by integrating AI into your daily work and career growth strategy. Attendees will leave with a clearer view of how AI is reshaping data careers and practical ideas for how to evolve their own skills, direction, and confidence in an era where AI is not replacing, but redefining, human expertise.