PyLadies of San Francisco

*** Please RSVP on Luma: https://luma.com/0qa8rm4z ***

Theme

​Building with AI agents presents unique challenges and opportunities. In this meetup, we'll explore practical solutions, lessons learned, and real world insights for using agents to supercharge your software engineering workflows.

​Tentative Agenda

• ​6:00 pm: Networking and Food
• ​7:00 pm: Welcome and Community Announcements
• ​7:05 pm: Sponsor Presentation from Datadog
• ​7:25 pm: Talk TBD (This could be you! DM your proposal!)
• ​7:50 pm: Talk TBD
• ​8:15 pm: Networking
• ​9:00 pm: End of event

Event Sponsors

*** Please RSVP on Luma: https://luma.com/693643qu ***

Join us for an evening of Python, Data Science and networking. A big thank you to Snowflake for sponsoring our meetup!

Theme: How is data science/analysis changing alongside AI? The session is meant to explore experience/opinions on how the role is evolving, what skills remain essential, system designs, and how teams are adapting.

​Speakers:

• ​Rose Tan, Staff Data Scientist, Snowflake
  Rose has over a decade of experience in causal inference and experimentation and holds a PhD in Economics from Stanford University. Her goal is to use data to drive business strategy, and she enjoys using AI to reinvent the data science job description. At Snowflake, she works on B2B platform products and brings extensive experience in consumer-focused data science from her time at LinkedIn.
• ​Kasia Rachuta, Senior Staff Data Scientist, Intuit
  Kasia is a Senior Staff Data Scientist at Intuit, where she works on payments and uses AI daily to sharpen how her team builds and decides. Her expertise spans identity verification, payments, sales analytics, ecommerce, and infrastructure. Previously, she was a Data Science Tech Lead at Square, and before that worked at Medium and FiveStars, where she ran numerous A/B tests to inform product decisions and contributed to company-wide experimentation initiatives. In her free time, she enjoys travel, scuba diving, and reading.
• ​Lilinoe Harbottle, Biomedical Engineering Researcher Data Systems, VC-Backed Startup
  ​Leveraging a background in software delivery at Auris Health, Lilinoe engineers data infrastructure to advance healthcare technology. She specializes in implementing robust validation layers to ensure system trust and compliance in highly regulated environments.

​Tentative Agenda:

• ​6:00 pm: Check-in + Networking
• ​6:15 pm: Welcome and Community Announcements
• ​6:45 pm: Rose Tan (25 min, 5 min Q&A)
  Topic: How I AI: A Data Scientist's Perspective
• ​6:55 pm: Kasia Rachuta (25 min, 5 min Q&A)
  ​Topic: The Data Scientist's Job in the Age of AI: What Changed, What Didn't
• ​7:20 pm: Lilinoe Harbottle (30 min)
  Topic: Trust in the Loop: System Design and Data Integrity in Regulated Environments
  ​Description: In regulated fields like MedTech, unverified automation introduces severe operational liabilities. This session runs a practical post-mortem on a silent data pipeline failure to isolate where automated logic drifted from compliance requirements, offering a clear blueprint on how to build validation layers that protect production systems.
• ​7:50 pm: Wrap-up + Networking
• ​8:30 pm: Event ends

​Who should attend:
If you’re navigating your analytics career alongside AI, then this event is for you. Attendees are data scientists, data analysts, data engineers, product managers, technology contributors and leaders, or individuals interested in learning more about this space

Workshop Description

This is a one-day PyLadies workshop designed to help participants make their first contributions to Python open-source projects. The workshop will combine instruction on the open-source contribution process with guided, hands-on contributions to participating projects. The event will be designed primarily for new and aspiring open-source contributors, while more experienced contributors and project maintainers will have opportunities to mentor participants and introduce their projects to the community.

Event Agenda

• 9:00–9:30 — Arrival, breakfast & setup
  9:30–10:00 — Welcome + How Open Source Works
• 10:00–10:45 — Git & GitHub Contribution Workflow
• 10:45–11:00 — Break
• 11:00–11:45 — Navigating an Unfamiliar Python Project
• 11:45–12:30 — From Issue to Contribution
• 12:30–1:15 — Lunch
• 1:15–1:45 — Project Introductions
• 1:45–2:00 — Choose Projects + Get Set Up
• 2:00–4:15 — Guided Open-Source Contributions
• 4:15–4:45 — Review, Iteration & What Happens Next
• 4:45–5:15 - Show & Tell + Wrap-Up