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.
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.
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Senior Data Scientist, Causal Inference
Lead causal inference and marketing mix modeling efforts to measure and optimize marketing investments for Lyft's Growth Products team. Requires 4+ years experience, advanced degree, and expertise in Python, SQL, and causal methods.
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 production environments.