Data Scientist
Builds AI agents and systems to automate end-to-end data science workflows, including analysis, querying, pipelines, and experiment interpretation. Requires 6+ years in data science/engineering with strong SQL, Python, and AI experience.
About the job
What You'll Do
- Accelerate the AI-native data workflow - turn what's working into repeatable systems, scalable tools, and patterns for the data team and company
- Build AI agents that do data science - conduct end-to-end analyses: explore data, form hypotheses, run queries, interpret results, generate recommendations
- Make the warehouse AI-readable - build semantic layer, context, retrieval infrastructure for accurate AI querying
- Automate the data lifecycle - self-healing pipelines, automated dbt model generation/validation, data quality agents
- Ship AI-powered experiment analysis - agents for A/B test interpretation, statistical flagging, ship/no-ship recommendations
- Own the full lifecycle - identify problems, prototype with LLMs, iterate, deploy, monitor
- Turn the data team into a product team - build internal data products with self-serve AI interfaces
What We're Looking For
- 6-8+ years in data science, analytics engineering, or related role
- Strong product sense - work with product/business teams, understand user behavior and metrics
- Deep SQL expertise - data modeling, warehouse experience
- Pipeline experience - build/maintain pipelines, dbt, data quality
- Software engineering chops - build/ship Python tools, APIs, deploy services
- Genuinely excited about AI - LLM building, agents, RAG, AI workflows
- Builder mentality - automate processes, ship fast
- Autonomy - define and execute roadmap
Bonus
- Experience with dbt (production models)
- Snowflake administration/optimization
- Built Slack bots, CLI tools, developer tools
- AI agent frameworks
- BI tools
- A/B testing/experimentation
- Early-stage startup experience
Skills
SQL, Python, dbt, Snowflake, AI Agents, LLMs, RAG, Data Pipelines, A/B Testing, Semantic Layer
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