Research Engineer - Causal AI
Designs and implements novel causal inference algorithms and production systems for marketing attribution challenges at enterprise scale. Requires 5+ years shipping research code, strong math/stats background, Python proficiency, and customer collaboration.
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
Requirements
Applied Science & Engineering
- 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
- Communication skills - can explain complex technical concepts to varied audiences
Domain & Advanced Skills
- 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
- Understanding of ML engineering and MLOps practices
- Ability to work directly with customers on technical problems
- Experience with both Bayesian and frequentist statistical methods
Nice to Haves
- Published applied research or technical writing
- Experience in consulting or customer-facing technical roles
- Background in operations research or decision sciences
- Familiarity with GPU computing and performance optimization
- Understanding of privacy-preserving analytics and differential privacy
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