Data Scientist

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

Were looking for someone whos been a great data scientist, analytics engineer, or data engineer - the kind of person who knows which metric actually matters, who can design an A/B test that answers the real question, whos gone deep on a data model because something didnt add up - and who has decided that the highest-leverage thing they can do next is build AI systems that fundamentally change how data science gets done.

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

Youll join a data team thats already using AI across its workflows - but we know theres a much bigger opportunity ahead. We have buy-in from leadership to make it happen. Now were building a team dedicated to taking what weve started and turning it into something world-class: scalable systems, new tools, and an AI-native way of working that doesnt just make us world-class - but pushes the entire industry forward.

What Youll Do

Accelerate the AI-native data workflow - the team is already working this way. Youll take whats working and turn it into repeatable systems, scalable tools, and patterns that the data team and the entire company can adopt.

Build AI agents that do data science - not just answer SQL questions, but conduct end-to-end analyses: explore data, form hypotheses, run queries, interpret results, and generate actionable recommendations.

Make the warehouse AI-readable - build the semantic layer, context, and retrieval infrastructure that lets any AI system (internal or product) query Perplexitys data accurately and reliably.

Automate the data lifecycle - self-healing pipelines, automated dbt model generation and validation, 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, to prototyping with LLMs, to iterating on accuracy and UX, to production deployment and monitoring.

Turn the data team into a product team - build internal data products that stakeholders across the company actually use daily, replacing ad-hoc requests with self-serve AI interfaces.

Were Looking For

6-8+ years in data science, analytics engineering, or a related role - youve been in the data trenches.

Strong product sense - youve worked closely with product and business teams, you understand what drives user behavior, and you have good instincts for what to measure and what to build.

Deep SQL expertise - you think in SQL, youve built data models, you know your way around a warehouse.

Pipeline experience - youve built and maintained data pipelines, worked with dbt, dealt with data quality issues firsthand.

Enough software engineering chops to be dangerous - you can build and ship a working tool in Python, not just a notebook. You can wrangle APIs, deploy a service, write code that other people can maintain.

Genuinely excited about AI - youve been building with LLMs on your own time. You have opinions about which models are good at what. Youve tried building agents, RAG systems, or AI-powered workflows.

Builder mentality - you see a manual process and you cant help but automate it. You ship fast and iterate.

Autonomy - this is a new function. Youll define the roadmap as much as execute it.

Bonus:

Experience with dbt (building and maintaining production models)

Snowflake administration and optimization

Youve built Slack bots, internal CLI tools, or developer productivity tools that people actually used

Background in AI agent frameworks

Experience with BI tools - you know whats worth automating because youve done the manual version

A/B testing and experimentation - youve designed experiments and analyzed results

Early-stage startup experience

Why This Role

Set the standard for the industry - the team is already using AI across its work. Youll be the one who turns that into something other data orgs look to as the benchmark.

Recursive AI - Perplexity builds an AI answer engine for the world. Youll build one for the company.

Few places offer this kind of alignment between the product and the work.

Frontier models, day one - youre at an AI company with access to frontier infrastructure and people who deeply understand whats possible.

Massive leverage - the systems you build will multiply the output of every data team member and every stakeholder who needs data.

Direct impact - small team, no layers of approval. Idea to shipped system in days, not quarters