Data Scientist, Causal Inference & MMM (Growth Products)
Data Scientist, Causal Inference & MMM (Growth Products)
Lyft is seeking a Data Scientist with expertise in causal inference and marketing mix models to lead the measurement and optimization of marketing channel investments. This role involves developing and deploying data science solutions, building statistical pipelines, and designing experiments within the Growth Products team.
About the role
About the Role
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 within the Growth Products team. The Growth Products team at Lyft is dedicated to driving rider and driver acquisition, scaling the business, and balancing the marketplace through incentive and messaging targeting, budget optimization, and paid media measurement.
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.
Experience
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 (MMM) is highly preferred.
Expertise in SQL and experience with large-scale data platforms.
Proficiency in Python and working within production coding environments.