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Alembic is looking to solve marketing's hardest problem: proving what actually works. The company aims to build trusted systems that Fortune 100 companies use to make multimillion-dollar decisions by decoding the chaos of modern marketing.

Requirements

• 5+ years developing and shipping research code in production environments
• Strong mathematical background - statistics, probability, optimization, causal inference
• Proficient Python developer - can write production-quality code, not just notebooks
• Causal inference expertise - practical experience applying causal methods to real problems
• Data-intensive systems - experience processing and analyzing large datasets
• Research to production - track record of turning research ideas into shipping features
• Experience with both Bayesian and frequentist statistical methods

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
• 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
• Document research and implementation decisions for reproducibility and knowledge transfer

Other

• MS or PhD with significant applied research experience
• Background in econometrics, statistics, or computational social science
• Experience in marketing analytics, A/B testing, or measurement domains
• Ability to work directly with customers on technical problems
• Communication skills - can explain complex technical concepts to varied audiences