Overview In this role you apply causal ML to pricing at scale, building end-to-end pipelines that produce interpretable, production-ready causal estimates. You bridge econometric concepts with ML workflows to enable economists and engineers to ship impactful pricing improvements. You will own heterogeneous treatment effect analysis and contribute reusable causal tooling that informs pricing experiments and LTV-related decisions. This is a hands-on, deployment-focused role with meaningful business impact and collaboration across economists, SDEs, and PMs.
Compensation / Benefits- health insurance (medical, dental, vision)
- retirement plan with 401(k) matching
- paid time off
- parential leave
- RSUs / sign-on payments
- comprehensive benefits package
Responsibilities- Build end-to-end causal ML pipelines for pricing use cases
- Own the science of heterogeneous treatment effects: identification, model selection, evaluation, and tradeoffs between econometric and ML approaches
- Support pricing experiment analysis and develop reusable tooling for economists to use without ML expertise
- Define business metrics upfront and deliver evaluation reports on pricing errors avoided and LTV changes
- Evaluate and adopt novel causal inference techniques (e.g., synthetic DiD, generalized random forests, causal representation learning) and write internal proposals
- Write internal documentation and methodology papers, ensuring pipelines are extensible and well-documented for others
- Collaborate with Sr. Economist on identification strategy and with SDE/DE teams on production deployment; align with PMs on experiment design
Key requirements- PhD or Master's degree with 4+ years in CS, CE, ML or related field
- Programming experience in Python, Java or C++
- Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing
- Collaborative and cross-functional communication
- Strong written communication and documentation
- Problem-solving mindset and bias toward shipping production solutions
- Python
- Java
- C++
