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 marketing mix modeling is highly preferred.
Expertise in SQL and experience with large-scale data platforms.
Proficiency in Python and working within production coding environments.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products.

As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels.

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.

Senior Data Scientist, Causal Inference

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