Product Data Scientist

Location

San Francisco

Full time

On-site

Marketing

• $175K – $195K
  • Offers Equity

• Generous equity grant
• 401k matching
• Relocation bonus
• Health, vision, dental insurance

Wispr Flow is making it as effortless to interact with your devices as talking to a close friend.

Today, Wispr Flow is the first voice dictation platform people use more than their keyboards — because it understands you perfectly on the first try. It’s context-aware, personalized, and works anywhere you can type, on desktop or phone.

In 2026, in addition to dictation, we're focused on building native actions — an agentic framework that understands you, and works reliably.

We’re a team of AI researchers, designers, growth experts, and engineers rethinking human-computer interaction from the ground up. We value high-agency teammates who communicate openly, obsess over users, and sweat the details. We thrive on spirited debate, truth-seeking, and real-world impact.

We're grown our revenue +150% every quarter for the last 4 quarters, and have raised $81M from Tier 1 VC firms and other well-known angels.

We're looking for a Product Data Scientist to be the analytical backbone of our product and growth team. You'll work directly alongside PMs, engineers, and our analytics team to turn data into product decisions - from instrumentation and experimentation to funnel analysis and growth modeling.

This is not a reporting role. You'll own the analytical layer of how we understand user behavior and help us build the data intuition that drives product strategy.

• Build and own core product and growth metrics: activation, retention, engagement, and conversion - with particular depth on the nuances of a cross-platform, PLG consumer product
• Proactively surface insights - patterns in usage cohorts, feature adoption signals, product funnel drop-offs, engagement inflection points
• Partner with product managers and engineers across our core product surface areas to define and answer the questions that drive decisions
• Analyze A/B experiments end-to-end - from hypothesis formation through to causal interpretation and recommendations
• Collaborate closely with analytics engineers on our dbt + Click House stack to ensure metric definitions and data models are clean, consistent, and align with business and product processes

• 5+ years of experience in data science or quantitative analytics, with meaningful time spent at a consumer SaaS or consumer tech company
• Experience with experimentation - from hypothesis design through analysis, with the ability to build frameworks that let the product team run and learn from tests at scale
• Strong SQL skills and fluency working within a modern data stack (dbt, Click House, Snowflake, or similar);
  Python proficiency for analysis and modeling
• Experience with embedded with product teams, using sound judgment in ambiguous situations to shape priorities and deliver actionable analysis
• Clear communicator who can make complex analysis legible to non-technical stakeholders

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Compensation Range: $175K - $195K