Head of Data Science

Job Description

You are looking for an exceptional Lead Data Scientist to build and lead a world-class Data Science team that drives meaningful business outcomes at scale. This is not a pure people-management role. It is a high-ownership, player-coach role for someone who can think strategically, execute aggressively, and lead from the front. You will be expected to identify the highest-leverage opportunities across the business, shape the ML roadmap, drive rapid experimentation, and ship production-grade ML systems that materially move core metrics. If you have a strong track record of building and deploying machine learning systems in production, leading high-performing teams, and solving ambiguous, high-impact business problems, and are comfortable switching between leadership, architecture, hands-on debugging, stakeholder alignment, and execution review, sometimes on the same day, then this role is for you. If youre excited by messy real-world problems, high scale, fast decisions, and building with intensity, this role will be a great fit for you.**Key Responsibilities:**- Set the bar for what great looks like in applied Data Science and ML execution across the organization.- Define and drive the Data Science roadmap by identifying the highest-impact problems worth solving, not just the loudest asks.- Lead, hire, and grow a high-caliber team of Data Scientists / ML Engineers with a culture of ownership, urgency, and technical excellence.- Own end-to-end delivery of ML initiatives.**Qualifications Required:**- Strong track record of building and deploying machine learning systems in production.- Experience leading high-performing teams.- Ability to solve ambiguous, high-impact business problems.- Comfortable switching between leadership, architecture, hands-on debugging, stakeholder alignment, and execution review.This role offers you the opportunity to disrupt the 500-year-old industry with technology at its core, and be a part of building the worlds most valuable restaurant company on the internet. You are looking for an exceptional Lead Data Scientist to build and lead a world-class Data Science team that drives meaningful business outcomes at scale. This is not a pure people-management role. It is a high-ownership, player-coach role for someone who can think strategically, execute aggressively, and lead from the front. You will be expected to identify the highest-leverage opportunities across the business, shape the ML roadmap, drive rapid experimentation, and ship production-grade ML systems that materially move core metrics. If you have a strong track record of building and deploying machine learning systems in production, leading high-performing teams, and solving ambiguous, high-impact business problems, and are comfortable switching between leadership, architecture, hands-on debugging, stakeholder alignment, and execution review, sometimes on the same day, then this role is for you. If youre excited by messy real-world problems, high scale, fast decisions, and building with intensity, this role will be a great fit for you.**Key Responsibilities:**- Set the bar for what great looks like in applied Data Science and ML execution across the organization.- Define and drive the Data Science roadmap by identifying the highest-impact problems worth solving, not just the loudest asks.- Lead, hire, and grow a high-caliber team of Data Scientists / ML Engineers with a culture of ownership, urgency, and technical excellence.- Own end-to-end delivery of ML initiatives.**Qualifications Required:**- Strong track record of building and deploying machine learning systems in production.- Experience leading high-performing teams.- Ability to solve ambiguous, high-impact business problems.- Comfortable switching between leadership, architecture, hands-on debugging, stakeholder alignment, and execution review.This role offers you the opportunity to disrupt the 500-year-old industry with technology at its core, and be a part of building the worlds most valuable restaurant company on the internet.

Keyskills :
Data ScienceMachine LearningDemand forecastingInventory forecastingCapacity planningBusiness reportingDecision supportML modelsOptimization systemsRule enginesDecision frameworksMarketing spend optimizationDelivery time predictionLogistics