Alembic
Research Engineer - Causal AI
San Francisco HQ
Sponsorship not specifiedDetected 288 days ago
PythonAlgorithmsMachine LearningMLOpsStatisticsA/B TestingMarketing AnalyticsResearchLeadershipCommunicationWriting
About the role
- We're looking for an Applied Scientist who solves hard mathematical problems in marketing attribution through both algorithmic innovation and production-quality implementation.
- This role is ideal for someone who wants to apply deep technical expertise to real-world problems-shipping code that makes a difference, not just publishing papers.
Responsibilities
- Design and implement novel approaches to marketing measurement problems, shipping working code
- Build production systems for causal inference that maintain statistical rigor at enterprise scale
- Develop algorithms that are both mathematically sound and computationally efficient
- Document research and implementation decisions for reproducibility and knowledge transfer
- 5+ years developing and shipping research code in production environments
- If you only want to tell people what to build instead of building and coding alongside them, we're not the environment for you
Requirements
- Experience with both Bayesian and frequentist statistical methods
Company info
- Collaborate with customers to understand their measurement challenges and develop technical solutions
- Create tools and libraries that enable both internal teams and customers to leverage advanced analytics
- Though we have real paying customers and a playbook for growth, we proudly remain an early-stage startup
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