About the job
About Decagon
Decagon stands at the forefront of conversational AI, enabling brands to create unparalleled concierge customer experiences.
Our innovative technology empowers leading enterprises such as Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to harness AI agents that facilitate personalized and highly engaging interactions across various channels, including voice, chat, email, and SMS.
We envision a future where customer experience transcends traditional support methods, offering quicker solutions, enriched dialogues, and more profound connections. Backed by elite investors like a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, we are committed to this vision.
At Decagon, we thrive in an office environment that champions collaboration, excellence, and rapid progress. Our core values—Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle—guide our team dynamics and growth.
About the Role
In your role as a Senior Data Scientist at Decagon, you will apply rigorous technical expertise to analyze, test, and leverage data across our business operations. You will design experiments, utilize advanced statistical techniques, and construct scalable analytical frameworks to directly influence product strategy and enhance corporate performance.
You will collaborate with Engineering and Product teams to implement robust measurement practices, promote data-driven decision-making, and derive insights that will guide Decagon’s future direction. This position requires a blend of analytical excellence and product insight, with the capacity to impact decisions at the highest organizational levels.
In this role, you will
Develop and manage foundational datasets and metrics that reflect usage, performance, and efficiency across Decagon's AI platform.
Enhance and expand Decagon’s data models, metrics, and dashboards to ensure coherent and scalable reporting across various teams.
Collaborate closely with Engineering to inform strategy using data—identifying potential bottlenecks and scaling challenges before they escalate.
Partner with Product and Engineering teams to integrate experimentation and measurement best practices into product development processes.
Continuously refine Decagon’s data stack, ensuring efficient models, pipelines, and tools that enable self-service analytics across the organization.

