Senior Data Scientist, Product Intelligence

fal•San Francisco, CA

About The Position

As a Senior Data Scientist for Product Intelligence, you will architect the analytical foundation for how fal builds and grows. Your domain spans the entirety of the developer journey—from initial acquisition to long-term expansion. You will turn raw behavioral and system signals into the metrics and insights that shape our product roadmap and go-to-market strategy. This is a high-influence role where you will act as a strategic partner to Product, Engineering, and Marketing. Beyond domain-specific analysis, you will share ownership of the foundational data systems, standards, and experimentation frameworks that serve as the source of truth for the entire company.

Requirements

5+ years of experience in data science or analytics roles-ideally with API products, developer tools, or B2B SaaS platforms
Advanced-level SQL and proficiency in Python for analytics, modeling, and experimentation
Strong proficiency with dbt and orchestration tools like Dagster or Airflow for production pipeline
Proven ability to work across teams to influence product roadmap and strategy
Experience establishing data quality and governance practices, including lineage, testing, and documentation.
Demonstrated bias for action and the ability to thrive in fast-moving, ambiguous environments.
A track record of shipping data products or features, not just dashboards. You think like a Product Manager and build like an Engineer

Nice To Haves

Experience working on developer-facing products or platforms.
Exposure to infrastructure, performance, or cost-related data (e.g., cloud usage, compute efficiency).
Experience operating in early-stage or fast-scaling environments.
Interest or experience in architecting data systems designed for agentic consumption and AI-driven product workflow

Responsibilities

Architect the metrics that define user success on fal and build the measurement systems to track activation, retention, and time-to-value across both our self-serve and B2B pipelines.
Develop a deep, causal understanding of how customers discover, adopt, and grow on the platform to identify key expansion levers and acquisition opportunities.
Own the instrumentation standards and data contracts that serve as the source of truth for product telemetry and core behavioral schemas.
Surface insights through rigorous deep-dives and experimentation to influence product direction, pricing models, and go-to-market initiatives.
Develop scalable data products including automated experimentation frameworks and canonical schemas that enable teams to self-serve and move faster.