About the job
Join our dynamic Analytics team at DoorDash, where we are seeking an innovative Senior Lead Data Scientist to spearhead the exploration and interpretation of complex data sets. This pivotal role will help shape our global platform expansion strategies, driving informed decisions across all facets of our organization.
About the Team
The Analytics team is dedicated to leveraging advanced analytical methodologies to inform strategic initiatives and operational decisions. As a Senior Lead Data Scientist, you will play a crucial role in transforming insights into actionable strategies that contribute to DoorDash’s success.
About the Role
In this role, you will delve into intricate data analyses to tackle significant business challenges, devise and implement experiments based on your findings, and collaborate with cross-functional teams to enact meaningful operational changes. Your expertise will be crucial in enhancing our marketplace efficiencies, optimizing customer acquisition, and addressing fraud prevention among other exciting challenges.
If you thrive on identifying patterns in data chaos, possess a passion for building impactful market strategies from the ground up, and have a proven track record of employing analytics to drive revenue and operational growth, we want to hear from you!
Your Impact
- Lead and mentor a team of Data Scientists in uncovering vital business insights while also contributing as an individual expert.
- Shape the Product and Operations roadmap with data-driven recommendations.
- Engage with senior leadership to present your team's findings and address complex business challenges.
- Establish measurement strategies for your area, defining key performance indicators and best practices in experimental design and statistical analysis.
- Craft a strategic learning roadmap informed by data insights, key questions, and hypotheses.
Qualifications
- A Master’s or Ph. D. in Mathematics, Physics, Statistics, Economics, Computer Science, or a related field.
- 8+ years of experience in Data Science, with a focus on product analytics and operational strategies.
- Proficiency in statistical tools and programming languages such as Python, R, or SQL.
- Strong analytical mindset with a demonstrated ability to solve complex problems using data.
- Excellent communication skills with the ability to convey complex findings to non-technical stakeholders.

