Senior Manager, Analytics, Customer Experience

DoorDash USA•Los Angeles, CA

2d•$219,700 - $323,000

About The Position

The Customer Experience team serves as a foundational operations pillar at DoorDash, dedicated to resolving friction within the last mile. We architect and oversee an expansive global network of support centers — spanning both teammate-assisted and AI-driven support — obsessing over the user journey to ensure every interaction is seamless and reliable. As the analytics team, our mission is to make every support interaction measurably better: we define what a great resolution looks like, quantify where we fall short, and turn that into a roadmap for product, operations, and AI/ML partners. We are looking for a Senior Manager to lead and grow the analytics team behind our core support experience. As a Senior Manager on the Customer Experience Analytics team, you'll set the analytical vision for how DoorDash measures and improves customer resolutions across our support channels. You'll lead and grow a team of data scientists working at the intersection of customer experience quality and operational cost — uncovering opportunities to drive perfect interactions, informing improvements to teammate tooling, and shaping how we deploy and evaluate AI-driven support. You'll establish a clear measurement framework for resolution quality, own insights to drive strategy and roadmap, and align partners across CX, Product, Engineering, Operations, and AI/ML. This is a high-visibility leadership role: success means better outcomes for customers, a more effective support organization, and a team of data scientists who are growing in their craft.

Requirements

8+ years of experience in data science, product analytics, consulting, or a related field, with the executive communication skills required to translate data into business impact.
3+ years of experience as a people manager, with a track record of developing data scientists and building high-performing teams.
A degree in Math, Statistics, Economics, Computer Science, or a similar quantitative domain.
Deep expertise in SQL, experimentation and A/B testing, and statistical analysis (e.g. hypothesis testing, regression modeling).
Strong technical judgment — the ability to lead through your technical chops and apply them appropriately in a business context.
Experience with data pipelines and partnering with data and product engineers to build robust data foundations.
Comfort balancing quality and efficiency, ideally in a customer support, operations, marketplace, or service-delivery context.
Excellent communication and cross-functional skills, including the ability to present complex findings to non-technical audiences and influence strategic decisions.

Nice To Haves

Experience measuring AI, LLM, or automation-driven products in a production setting.

Responsibilities

Lead, grow, and develop a team of data scientists — providing mentorship, feedback, and clear career development pathways.
Set the analytical vision for the core support experience, defining what a great customer resolution looks like and building the metrics to measure it across teammate-assisted and AI-driven channels.
Uncover opportunities to drive perfect interactions, translating patterns in contact and resolution data into a prioritized roadmap for product and operations partners.
Inform improvements to teammate tooling and workflows, and quantify the tradeoff between customer experience quality and operations cost.
Partner with AI/ML teams to measure and improve automated support — designing evaluation frameworks for AI resolution quality, deflection, and escalation.
Drive measurement strategy for the area under scope, setting best practices around experiment design, statistical analysis, and success metrics.
Interface frequently with senior leadership across CX, Product, Engineering, and Operations to showcase your team's work and shape strategy with data.