Member of Data Staff (Data Acceleration)

Details

Perplexity is looking for a data professional to build AI systems that fundamentally change how data science gets done. The role focuses on building AI agents and internal systems that can handle end-to-end analysis workflows, including forming hypotheses, writing and running queries, interpreting results, and drafting recommendations with appropriate evaluation, review, and guardrails.

The role will also involve building retrieval infrastructure and evaluation loops for reliable warehouse querying, creating workflows to detect and diagnose data issues, and developing infrastructure that increases the output of a small data team.

Responsibilities

• Build AI agents that can safely explore data, form hypotheses, run queries, interpret results, and generate actionable recommendations with clear evaluation and human review loops.
• Build retrieval infrastructure and evaluation loops that enable AI systems to use semantic context and metadata accurately when querying the data warehouse.
• Turn AI-assisted workflows into repeatable systems, reusable tools, and patterns for the data team.
• Automate the data lifecycle through self-healing pipelines, automated dbt model generation and validation, data quality agents, and diagnosis workflows.
• Build AI-powered experiment analysis systems that interpret A/B test results, flag statistical issues, identify likely drivers, and draft ship/no-ship recommendations.
• Build internal data products and self-service AI interfaces that stakeholders use in place of ad hoc requests.
• Own the full lifecycle of projects, from identifying high-leverage problems and prototyping with LLMs to evaluating accuracy, designing the user experience, shipping to production, and monitoring quality over time.
• Help define the roadmap for this new function while executing against it.

Requirements

• 6+ years of experience in data science, analytics engineering, data engineering, or a related role.
• Deep SQL skills and strong analytics judgment, including experience with metrics, experiments, data models, and complex warehouse environments.
• Strong product sense and the ability to understand stakeholder needs, create adoptable workflows, and turn prototypes into products.
• Hands-on experience with frontier models, agents, retrieval-augmented generation (RAG) systems, evaluations, or AI-powered workflows.
• Experience with dbt, warehouse schemas, data quality issues, and the practical tradeoffs involved in building durable data systems.
• Builder mentality, with a focus on systematizing manual processes, shipping quickly, measuring quality, and iterating.
• Ability to work autonomously and help define the roadmap for a new function.

Bonus Qualifications

• Experience building production AI agents or agent evaluation systems.
• Experience with Snowflake, semantic layers, or metadata systems.
• Experience building internal tools, Slack bots, command-line interfaces, or developer productivity products that people used.
• Strong experimentation background, including metric design and statistical interpretation.
• Experience with business intelligence tools and judgment about what should be automated versus kept human-reviewed.
• Early-stage startup experience.

Benefits

Full-time U.S. employees receive a comprehensive benefits program including equity, health, dental, vision, retirement, fitness, commuter and dependent care accounts, and more. Full-time employees outside the U.S. receive a benefits program tailored to their region of residence. USD salary ranges apply only to U.S.-based positions; international salaries are set based on the local market. Final offer amounts depend on multiple factors, including experience and expertise.