Staff Product Analyst

Deepgram

31d

About The Position

Deepgram is looking for a Staff Product Analyst to accelerate our evolution from a single-product transcription company to a comprehensive voice AI platform. You'll be the first product analyst on our team, reporting to our VP of Product and partnering directly with product managers and designers to build the measurement infrastructure and experimentation frameworks that help us scale self-serve and product adoption. As the founding analyst, you'll establish the analytics foundation for our product team—building pipelines, defining frameworks, and creating the systems that help product managers, designers, and engineers make faster, and more impactful decisions. You'll start with a laser focus on our self-serve funnel, driving conversion from signup to first programmatic API/SDK request, knowing that this optimization directly feeds both self-serve revenue and sales-qualified leads. As you establish this foundation, your scope will expand to help identify patterns across our multi-product portfolio and inform strategic investment decisions.

Requirements

Staff-level expertise in product analytics, with proven ability to lead analytics strategy (we care more about expertise and leadership than years of experience)
Demonstrated track record of accelerating self-serve or PLG growth at a previous company, particularly driving conversion in developer-focused products
Strong SQL skills and hands-on experience working directly with data warehouses
Proven ability to build dashboards and analytics infrastructure yourself—you don't need a data engineering team to be effective
Deep experience designing, running, and analyzing experiments with statistical rigor
Understanding of developer behavior and API/SDK adoption patterns—you know what signals matter for programmatic usage
Experience being the first or founding analyst on a team—comfortable building everything from scratch
Leadership presence to establish best practices and mentor PMs on data literacy
Excellent communication skills to translate technical findings into strategic recommendations for executives

Nice To Haves

Experience with Superset and Heap Analytics (or similar tools like Mixpanel, Amplitude, Looker, Mode)
Background in B2B SaaS with both self-serve and enterprise motions
Understanding of multi-product portfolio dynamics and how to measure cross-product patterns
Experience with usage-based pricing models or real-time streaming data products
Deep knowledge of product instrumentation and event tracking best practices
Expertise in advanced statistical methods beyond basic A/B testing (causal inference, cohort analysis, time-series analysis)
Experience working in voice AI, ML/AI platforms, or developer tools

Responsibilities

Own the analytics strategy for self-serve growth—design experiments, build measurement infrastructure, and drive insights that increase conversion from signup to first programmatic request
Build robust, repeatable analytics pipelines and dashboards from the ground up using Superset and Heap Analytics
Partner directly with product managers and designers to define success metrics, establish baselines, and instrument products correctly
Design and analyze experiments across the developer journey, with deep understanding of API/SDK adoption patterns
Collaborate with analytics partners in Marketing and Sales to connect product usage signals with acquisition, activation, and downstream sales outcomes, building a holistic view of the end-to-end PLG funnel
Surface patterns in product usage across our growing portfolio to identify high-value use cases, customer segments, and where to double down on investment
Serve as the analytical partner to Product leadership: synthesize insights across multiple products and use cases to identify patterns that inform longer-term product strategy and investment decisions
Establish experimentation best practices and analytical rigor as the team scales PLG motions
Translate complex findings into clear, actionable recommendations that shape product roadmap and investment decisions
Build the analytics muscle for the team—creating frameworks and systems that enable PMs to self-serve insights while you focus on strategic analysis