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6th percentile
Data scientist at Google DeepMind working on Gemini
Credibility
GTM / Distribution · 17th percentile
- deepmind.google ranks #2,843 on the Majestic Million (global domain prominence).
Relationship Matrix
Founder score
- 95%Probability of being accurate (95%)deepmind.google ranks #2,843 on the Majestic Million (global domain prominence).
What you likely need
You're a data scientist working at the frontier of AI at Google DeepMind on Gemini, with a strong research background (PhD in Pharmacology, postdoc at UCSF) and industry experience across Twitter and Yahoo. Founder Festival events focused on AI practitioners, applied ML, and the intersection of research and product would be most relevant to your current trajectory. Connecting with other technical operators building in the AI space — especially those bridging academia and industry — would be high-value.
Would you attend these IRL Festival events?
We will tune and customize your Founder Festival experience to make sure you get invited to the events that would be most valuable to you.
- introsA dinner for AI/ML practitioners at frontier labs (DeepMind, OpenAI, Anthropic, Google Brain) to exchange notes on applied research-to-product pipelines.
- positioningA roundtable for PhD-trained data scientists who transitioned into industry roles to discuss career paths from academia to frontier AI companies.
- tacticalA workshop for builders working on LLM evaluation, data quality, and product integration at large AI labs to share tooling and methodology.
- introsA Twitter/X alumni happy hour in NYC to reconnect with former colleagues now building or investing in AI and consumer tech startups.
- introsA NYC-based networking night for AI researchers and data scientists at major tech companies to explore early-stage startup opportunities and co-founder connections.
- positioningAn office hours session with technical founders who made the leap from senior IC data scientist roles to founding AI-native startups.
- tacticalA dinner for applied ML practitioners focused on the product side of AI — evaluation frameworks, user research, and shipping models to millions of users.