Search the 6 jobs at Lyft

As a Data Engineer at Lyft, you'll develop robust data pipelines to enhance business decision-making. Your responsibilities include managing data transport, implementing data quality systems, developing ETL tools, and optimizing SQL and Spark jobs. You will lead projects from design to implementation, ensuring data reliability and collaborating with cross-functional teams.

The Staff Business Systems Engineer at Lyft is responsible for managing corporate systems' performance, implementing monitoring tools, creating automated workflows, developing software, configuring applications, and providing end user training. This role requires collaboration with business users, data migration, and system audits while employing agile methodology and leading various initiatives including system optimization and support for financial applications.

The Data Analyst for Growth Strategy & Analytics at Lyft will manage experimentation, dashboarding, and strategy related to acquisition and lifecycle growth levers. Responsibilities include analyzing data, proposing optimization strategies, and presenting insights to stakeholders.

As a Senior Data Scientist specializing in Machine Learning at Lyft, you will develop algorithms and mathematical models to optimize rideshare supply and demand, driving decisions with data. You will collaborate with cross-functional teams, conduct exploratory data analysis, and implement algorithms in production, playing a key role in enhancing product offerings and user experiences.

The Senior Software Engineer will design, develop, and maintain the data platform at Lyft, focusing on data reliability and governance using tools like Verity and Amundsen. Responsibilities include managing project deliverables, collaborating with stakeholders, and enhancing platform operations to support informed decision-making.

As a Senior Data Scientist at Lyft, you will develop algorithms and mathematical models to address optimization and prediction challenges within the rideshare platform. Collaborating with cross-functional teams, you will drive the science behind the matching system, perform data analysis, and communicate findings to influence critical business decisions.