Data Science Manager, Rider App

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 Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products.

We are seeking a Data Science Manager to translate data into the actionable insights and algorithms that improves Rider App experiences our rider loves. In this role, you’ll shape the vision and drive execution across conversion, personalization, and platform health, ensuring we build durable relationships with every rider. By partnering with cross-functional leaders in Pricing, Loyalty, and ML teams, you will evolve our platform for both existing riders and expanding to serve new segments (e.g., Lyft Silver, Teens).

This is a high-visibility, high-impact role with direct influence on Lyft’s ride experience across millions of riders and rides everyday. The ideal candidate will bring deep expertise in advanced analytics, machine learning, causal inference, experimentation; strong business acumen in two-sided marketplace contexts; and a proven track record of leading product data science teams in fast-paced, cross-functional environments.

• →Lead, mentor and grow a high-performing team of Data Scientists and Analytics, focusing on improving end-to-end Rider App experience (booking → waiting → pickup → in-ride → post-ride) with algorithm development, machine learning, experimentation and advanced analytics. 
• →Partner with Product Managers and Engineering leads to define the vision and roadmap for the Rider App experience (e.g., personalized UI, merchandising strategy), ensuring alignment with overall business strategy.
• →Lead and execute the data science vision and roadmap for initiatives across Rider App Experience. Raise the bar on scientific rigor.
• →Establish robust experimentation and causal inference frameworks to measure the business impact of new features in a two-sided marketplace.
• →Conduct deep analyses of complex, large-scale datasets to uncover opportunities for growth, operational efficiency, and improved rider experience.
• →Translate technical findings into actionable business insights for executive leadership.
• →Champion data-driven decision-making, ensuring that product and strategy decisions are informed by rigorous quantitative analysis.
• →Drive innovation by staying current with emerging research, technologies, and industry best practices in AI powered data science workflow.

• Master’s or PhD in a quantitative field (Statistics, Applied Math, Economics, Computer Science, Operations Research) or equivalent practical experience.
• 5+ years of progressive experience in data science, machine learning, optimization, or causal inference, including building complex science framework to guide critical business decisions 
• 2+ years of people management experience leading high-performing technical teams, with a proven ability to mentor, develop, and retain top talent.
• Demonstrated ability to set a strategic vision for data science and translate it into impactful, scalable solutions that drive measurable business outcomes.
• Deep expertise in experimental design, causal inference, machine learning, and statistical methodologies, with a track record of applying them to high-stakes product or marketplace decisions.
• Experience navigating complex, ambiguous problem spaces and guiding teams through prioritization, tradeoffs, and execution.
• Strong communication and influence skills, with the ability to engage both technical and executive stakeholders, align priorities, and build consensus.
• Hands-on proficiency with SQL, Python, large-scale data processing tools and machine learning frameworks
• Preferred Qualifications
  • Experience with consumer mobile apps, marketplaces, or two-sided platforms.
  • Familiarity with personalization, content recommendation, uplift modeling, or lifecycle management.