Data Analyst, Operations Planning

Lyft · New York, NY

Experience: staff

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. Data and analytics are at the heart of Lyft's products and decision-making. As a member of the Lyft Urban Solutions team, you will play a key role in shaping the future of bike & scooter share by leveraging data to improve the performance of our bikeshare and scooter markets across America. A successful candidate thrives in a dynamic and collaborative environment, has a natural curiosity, and isn’t afraid to dive deep. In this role, you will collaborate closely with Operations, Hardware, Software, Product and Finance teams to identify opportunities and gaps in performance. You will work in a fast-paced environment where your analytical insights will directly impact strategic decisions around hardware product development, staffing, and product changes, ultimately driving better performance and long-term investments in micromobility infrastructure. We’re looking for a passionate and driven Data Analyst to tackle some of the most complex and impactful challenges in micromobility. If you’re excited about shaping the future of urban mobility through data, we’d love to hear from you. Responsibilities: Partner with Product, Engineering, Data Science & Analytics, Operations, Finance and other cross-functional stakeholders on initiatives to improve operational performance Develop frameworks and scalable processes to streamline reporting, drive decision-making and prioritization Forecast operational requirements needed to maintain high service levels and meet contractual and financial targets Work with our bike & scooter share markets to deliver ongoing support and deep dive analyses on performance; monitor and diagnose performance and present findings to key stakeholders Collaborate with cross-functional teammates to tackle complex problems including: asset maintenance, system health and labor forecasting Exp

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