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Strategy & Operations Manager (Data Science & Analytics), Uber Eats

City Operations, Operations & Launch
in Santiago, Chile

About the Role

The Uber Eats Data Science & Fraud Operations Manager role is a unique opportunity to help expand one of Uber's newest services, Uber Eats. This is a critical role bringing together a three-sided marketplace and optimizing the food delivery process. This operations-driven role calls for a rare combination of creative problem solving, detail orientation, and interpersonal ability to manage internal stakeholders.

This is an intense business and this person will work within the local Operations team, but will also interact with the Regional Operations team, along with headquarters-based engineering, product, and process teams. This role will have direct responsibility for the sustainability and reliability of the Uber Eats Business.

What You'll Do

  • Fraud & Analytics - Use various data mining and statistics techniques to bring deeper understanding of courier, restaurant, and eater fraud drivers. Uncover hidden patterns and use data to challenge the status quo and drive teams to action
  • Develop & Optimize Analytics Assets - Scale new and existing risk-related analytical assets to allow the business to efficiently operate and realize growth. Analytical assets include dashboards, experiments, machine learning models, etc
  • Develop & Optimize Processes - Scale new and existing processes to allow the business to efficiently operate and realize growth; analyze the business to track and improve metrics and profitability
  • Strategy - Choose which projects you and the team should prioritize, and set a timeline to reach goals quickly
  • Role encompasses ability to coordinate initiatives and global and local levels, and find ways to effectively communicate to all levels of stakeholders (from most junior, up to highest level executives)
  • Be an owner - Take ownership of Uber Eats' risk in Chile and do everything you can to support and enhance the quality of our services; We expect you to be proactive and resourceful in order to remove road blockers and find creative solutions

What You'll Need

  • 3 years of high performing work experience in startup, strategy, operations, analytics, business development, or a variety of other specialty roles with demonstrated ability in quantitative fields but we will consider candidates with less experience if they meet our other requirements
  • Quantitative degree (MBA or MS/Bachelor's in engineering, mathematics, finance, economics, physics, etc.)
  • Data-driven decision making ability and sound business judgment through deep analytical thinking
  • A willingness to be "on the ground" working responsively with the local team and multi-market fraud review teams
  • Problem solving - Being able to solve problems that involve people, things, and processes by using logic, common sense and data. Identifying the root cause of a problem as opposed to focusing on the symptoms.
  • Advanced SQL knowledge (or willingness to learn fast!)
  • Ease and likes for programming
  • Desirable knowledge in predictive modeling (non-mandatory)
  • Experience creating and optimizing processes
  • Ability to take initiative in a constantly-changing work environment while maintaining flexibility and a collaborative attitude
  • Stakeholder Management
  • Professional proficiency in English and Spanish

About the Team

As part of the Uber Eats Team, you'll work closely with the General Manager, Account Management and Operations teams to support processes that scale and innovate Uber Eats from the ground up.

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.

EquidadChile

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