Senior Data Scientist, Causal Inference
Lead causal inference and marketing mix modeling efforts to measure and optimize marketing investments. Requires 4+ years experience, advanced degree, and expertise in Python, SQL, and statistical pipelines.
About the job
Responsibilities
- Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems.
- Own complex domains and develop long-term roadmaps to maximize business impact.
- Build statistical pipelines, write production code, and design/analyze experiments.
- Participate in the science on-call rotation to ensure automated campaigns operate successfully.
Requirements
- Advanced degree in statistics, economics, mathematics, or equivalent industry experience.
- 4+ years of industry experience in causal inference or data science.
- Proven ability to apply statistics to unstructured problems and deliver measurable results.
- Deep technical expertise in causal inference and tackling challenging measurement problems.
- Expertise in SQL and experience with large-scale data platforms.
- Proficiency in Python and working within production coding environments.
Nice-to-Haves
- Expertise in marketing mix modeling is highly preferred.
Skills
Causal Inference, Marketing Mix Modeling, SQL, Python, Statistical Modeling, Experiment Design, Data Science, Production Code, Large-Scale Data Platforms
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