Women in Data Science - New York City
Details
To attend - you must register here [https://community.widsworldwide.org/posts/wids-new-york-city-regional-conference-2026](101 Astor Place NYC, New York, 10003 · New York, NY)
What to Expect
- Land your dream Data Science Job: focused on real‑world career growth in data science
- Hands‑on technical workshops on Docling and Granite Agents
- Inspiring technical talks spanning AI, GenAI, healthcare, manufacturing, cybersecurity, sports analytics, and the future of work
- A career panel featuring professionals from industry and research sharing honest insights, lessons learned, and actionable advice
- Plenty of opportunities for networking and community building
More Details
Land your dream Data Science Job - Career Workshop by Ana Osorio-Alvarado, Niki Karanikola
Learn about:
- Resume building & interview preparation
- Navigating early and mid‑career transitions
Hands‑On Technical Workshops:
- Docling Workshop – practical document understanding and AI workflows with Sophia I, and Lillie Ng
- Granite Agent Workshop – building agentic AI systems with real use cases with Sanda Htyte and Cara Mulrooney
Featured Talks & Speakers Include
- Data Science in Sports - by Kelsey McDonald
- Lessons from Evaluating GenAI Projects - Samar Deen, PhD
- Chatbot Personalization in the Wild - Angelina Wang
- From Warehouses to Wellness: AI applications across Manufacturing & Healthcare - Parisa Babaali
- AI and the Future of Work - Zanele Munyikwa
- Strengthening Cyber Defense with AI - Sophia I.
Career Panel Hear directly from professionals across industry and research, including AI & data science leaders from IBM, Meta and others —sharing insights on skills, career paths, and what it really takes to succeed in the field.
Here are our panelists: Maria Alejandra Sanchez, Shirley Han, Srideepika Jayaraman, Milbert Kiggundu-Bentham, Panel Moderator: Vanishri Murali
Who Should Attend
Students and early‑career professionals
Experienced data scientists and ML engineers
Researchers, analysts, and AI practitioners
Anyone curious about applying data and AI to real‑world, high‑impact problems