Original listing text, shown exactly as published by the company.
What You'll Do
- 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
You'll Love This Role If You
- Have the seniority and leadership to define what "good" looks like for product analytics at Deepgram
- Get energized by being the first—building systems from scratch and establishing foundational practices
- Can balance deep analytical work with strategic pattern recognition across a multi-product portfolio
- Have strong opinions on experimentation methodology and PLG measurement, backed by experience
- Thrive in ambiguity and can define the right questions to ask, not just answer requests
- Love partnering closely with product leadership to shape strategy in real-time
- Bring natural customer empathy and curiosity, as well as openness to try new tools/AI workflows to maximize analytics efficiency
It's Important to Us That You Have
- 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
It Would Be Great If You Had
- 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
