Head of Decision Intelligence

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AI-Augmented Intelligence: In close partnership with functional leaders, architect and deploy agent-assisted intelligence systems that move beyond static dashboards. Build workflows that proactively reason across silos (e.g., correlating API latency with churn signals in Salesforce) to surface automated root-cause analysis and actionable recommendations.
Infrastructure Evolution: In close partnership with our Tech/Engineering team, co-evolve our data stack. Define the semantic layer and data contracts required to make our infrastructure agent-ready and highly reliable.
Unlock Audio Intelligence: Leverage Deepgram's own Voice AI models to ingest and structure thousands of hours of internal calls, turning unstructured audio into queryable insights for all functional teams.
Strategic Leadership: Act as the primary data partner to the CEO and Board. Define the "source of truth" for our complex, usage-based revenue models and provide the analytical backbone for long-term strategy — from pricing, packaging, and distribution to market entry and capital allocation.
Team Building: Recruit and lead a lean, elite team of AI-native engineers. Set a culture where manual, repetitive SQL tasks are viewed as automation bugs to be solved with code and agents.

You want to build the "brain" of a unicorn-stage AI company from the ground up
You're energized by ambiguity and moving fast with imperfect infrastructure
You believe dashboards are a stepping stone — agents and automated reasoning are the destination
You want direct access to the Founder/CEO and Board, where your work shapes company strategy
You're excited by a problem nobody else in the world can offer: unlocking intelligence from proprietary Voice AI models

7+ years in data/analytics roles, with 2+ years leading teams at high-growth technology companies
Expert-level proficiency in SQL and Python — equally comfortable in a Hex notebook or dbt model as in a boardroom presentation
Experience building agentic systems that can navigate a data warehouse autonomously — not just using LLMs to write SQL, but understanding where human judgment still matters
A founder's mindset: comfortable with "work-in-progress" infrastructure, pragmatic enough to deliver high-value insights today while iteratively improving the foundation
Deep experience with usage-based SaaS metrics: consumption patterns, gross margin per million tokens/hours, and NRR
A track record of leading teams where data infrastructure was evolving alongside the business — and you still enjoy getting your hands dirty in code