Member of Data Staff (Data Scientist)
San Francisco • FullTime
Posted 6mo ago
About the job
Perplexity is seeking a Data Scientist to translate product questions into clear, actionable decisions. This role involves collaborating across product, engineering, growth, design, and user research teams to analyze user behavior, establish key metrics, design experiments, and identify high-impact opportunities for the company. The data team operates with an AI-native approach, leveraging AI tools to enhance analysis, coding, hypothesis exploration, documentation, and workflow automation. The core of the role emphasizes critical judgment in asking the right questions, selecting appropriate metrics, designing effective tests, and determining when findings are sufficient to guide action.
Responsibilities
- Analyze user behavior to inform product roadmaps, accelerate adoption, and enhance user experience.
- Design, run, and analyze A/B tests, defining success metrics and translating findings into product recommendations.
- Develop and maintain metrics, guardrails, dashboards, and reporting workflows to monitor product and company health.
- Collaborate with engineering, product, growth, design, and user research teams to address ambiguous questions and drive decisions.
- Create reusable data assets, including tables, models, and documentation, to improve analysis efficiency and consistency.
- Utilize AI tools to automate recurring analyses, build AI-assisted workflows, and enhance documentation.
- Communicate findings, assumptions, uncertainties, and recommendations clearly to facilitate team decision-making.
Requirements
- 6+ years of experience as a data scientist or in a closely related role.
- Strong product sense with an understanding of user behavior, product tradeoffs, and connecting analysis to decisions.
- Expertise in SQL, including navigating complex data warehouses, reasoning about data grain and joins, and debugging data issues.
- Significant experience in designing, running, and analyzing A/B tests.
- Proficiency in using LLMs and AI tools to accelerate data science workflows.
- Experience building metrics and dashboards using tools like Omni, Mode, Hex, or Looker.
- Comfort with ambiguity, including structuring open-ended questions, executing analysis, and making clear recommendations.
- Demonstrated ability for end-to-end ownership, from problem definition to stakeholder adoption.