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 is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve performing rigorous product deep dives, identifying opportunities for product enhancements, and measuring the impact of new features. The Global Growth team is at the forefront of innovation at Lyft, focused on expanding Lyft beyond North American rideshare’s core products. This includes our premium Luxury modes and Livery drivers, building a unified Lyft presence internationally, and enabling Autonomous Vehicles (AVs) domestically and abroad. These teams are at the center of innovation and the future of Lyft’s growth, and this role would be directly shaping the strategic roadmap for these crucial areas. As an Analytics Lead, you will collaborate with our world class team of engineers, product managers, and designers to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product and marketplace changes, and is comfortable working with a highly cross functional team. This role will help define Lyft’s strategy for growing luxury modes, setting the strategic roadmap for pricing, driver pay, and product development. In this role, you will help us tackle problems such as: How should we be pricing our premium Luxury products? Who are our current Luxury riders and what segment is most likely to grow our rider base? How can we best merchandise Luxury rideshare products within the Lyft app? What product features or app changes would improve the rider experience and motivate riders to take more Luxury rides? How do coupons and incentives motivate riders and drivers in premium segments? What is the value of offering a higher quality experience? How can we measure it? What metrics can we create?
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Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed