Data Scientist

Details

Perplexity is AI for people who expect more. This role brings that same standard to how the data team works — with AI at the center of everything we do.

We're looking for someone who's been a great data scientist, analytics engineer, or data engineer — someone who knows which metric actually matters, can design A/B tests that answer the real question, has gone deep on a data model because something didn't add up, and who has decided the highest-leverage next step is to build AI systems that fundamentally change how data science gets done.

Not another text-to-SQL bot or another dashboard. You'll build AI agents that conduct full analyses autonomously — forming hypotheses, writing and running queries, interpreting results, and drafting recommendations. You'll make the entire data warehouse AI-readable so any system can query it accurately. You'll create self-healing pipelines that detect and fix data issues before anyone notices. You'll build infrastructure that turns a small data team into one that operates at 10x its size.

The data team already uses AI across its workflows. With leadership buy-in, this role will help turn those efforts into world-class, scalable systems, new tools, and an AI-native way of working.

Responsibilities

• Accelerate the AI-native data workflow by turning existing practices into repeatable systems, scalable tools, and patterns that the data team and company can adopt.
• Build AI agents that do end-to-end data science: explore data, form hypotheses, run queries, interpret results, and generate actionable recommendations.
• Make the warehouse AI-readable: build the semantic layer, contextual metadata, and retrieval infrastructure so internal/product AI systems can query company data accurately and reliably.
• Automate the data lifecycle: build self-healing pipelines, automated dbt model generation and validation, and data quality agents that detect, diagnose, and fix issues autonomously.
• Ship AI-powered experiment analysis: agents that interpret A/B test results, flag statistical issues, and draft ship/no-ship recommendations for product teams.
• Own the full lifecycle from identifying the highest-leverage problem, prototyping with LLMs, iterating on accuracy and UX, to production deployment and monitoring.
• Turn the data team into a product team by building internal data products and self-serve AI interfaces used across the company.

Requirements

• 6–8+ years in data science, analytics engineering, or a related role.
• Strong product sense; experience working closely with product and business teams and good instincts for what to measure and build.
• Deep SQL expertise; experience building data models and working with data warehouses.
• Pipeline experience: building and maintaining data pipelines, working with dbt, and addressing data quality issues.
• Software engineering proficiency sufficient to build and ship working tools in Python, wrangle APIs, deploy services, and write maintainable code.
• Practical experience or independent work with LLMs, agents, RAG systems, or AI-powered workflows; strong interest in AI and model tradeoffs.
• Builder mentality: automate manual processes, ship fast, and iterate.
• Ability to work autonomously and help define the roadmap for a new function.

Bonus

• Experience with dbt (building and maintaining production models).
• Snowflake administration and optimization.
• Built Slack bots, internal CLI tools, or developer productivity tools that were used.
• Background in AI agent frameworks.
• Experience with BI tools and manual analytics workflows.
• A/B testing and experimentation design and analysis experience.
• Early-stage startup experience.

Why This Role

• Set the standard for the industry by turning AI-native workflows into a benchmark other data orgs look to.
• Work on recursive AI: aligning Perplexity's product and internal AI systems.
• Access to frontier models, infrastructure, and people who deeply understand AI capabilities.
• High leverage: systems you build will multiply the output of the data team and stakeholders.
• Direct impact in a small team with rapid iteration from idea to shipped system.

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 comprehensive 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.