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Anmol Madan
Anmol Madan is a seasoned professional with over 15 years of experience dedicated to the intersection of technology, artificial intelligence, and healthcare. Currently serving as the Chief (Data) Scientist at Livongo Health, he has a strong background in leveraging data-driven solutions to enhance healthcare outcomes. Anmol is renowned for his role as the Co-founder & Founding CEO of Ginger.io, a pioneering company in on-demand behavioral health services.
Anmol Madan is revered for his leadership qualities, being a driving force behind long-term vision planning, product strategy development, executive team establishment, and effective go-to-market strategies. An expert in identifying growth opportunities and implementing scalable solutions, he possesses a people-centric approach to leadership that resonates through his work.
Anmol Madan pursued his education diligently, studying Bachelor Of Engineering at Pune University, Master Of Science at Massachusetts Institute Of Technology, and Doctor Of Philosophy at Massachusetts Institute Of Technology. His academic journey also includes studies at Loyola High School and the Department Of Technology, Savitribai Phule Pune University.
Throughout his career, Anmol Madan has held key positions in notable organizations including Livongo as Chief Data Scientist. He has also contributed his expertise as an Advisor And Mentor to Series A Digital Health Companies and as a Researcher at Mit Media Lab. Anmol's professional journey includes pivotal roles at Microsoft as a Product specialist and at Imetrico as the Co-Founder And Chief Technology Officer.
Highlights
We're growing and looking for a product manager. Someone with experience building products and UX/solutions for B2B healthcare, and ideally with some early employee/founder experience, Over 80% of our current team is technical (PhDs in AI/ML), data engineering, so this a great opportunity to build impactful products with a stellar technical team around you. https://lnkd.in/evhp4ZbM
It's often thought of as "plumbing," but sadly almost every RadiantGraph enterprise customer and health plan partner has shared how they're struggling just to understand what's happening in their member populations before they can deploy AI and personalization applications. A new case study from our team shows the power of "built-in" data engineering capabilities-- making messy, sparse, incomplete healthcare data usable.
