Overview
Join to apply for the Automation & Analytics Manager role at Uber .
At Uber Eats LatAm, our Automation & Advanced Analytics team is passionate about unlocking the power of data to solve real business problems. We focus on translating business needs into data science solutions, collaborating closely with teams across the region to drive impact on top-priority initiatives.
What You’ll Do
- Design, implement, and scale automation solutions to streamline operations and drive efficiency.
- Use advanced analytics and business intelligence techniques to uncover insights, identify opportunities, and influence decision-making.
- Prioritize and manage high-impact projects from concept to delivery, coordinating with cross-functional stakeholders along the way.
- Identify and advocate for new product features that improve the experience for Eaters, Couriers, and Restaurants on our platform.
- Collaborate with Product and Engineering teams as an Operations partner, contributing to scalable and standardized processes across global regions.
- Maintain ongoing processes in the automation portfolio, ensuring transparency, reliability, and stakeholder trust.
What You’ll Need
Minimum of 3 years of experience in operations, analytics, strategy, or a related field—ideally in fast-paced or high-growth environments.Strong technical foundation : Proficiency in Python, SQL, and optimization techniques.Professional-level English proficiency.Problem-solving mindset that combines data, business acumen, and structured thinking.Proactive, flexible, and collaborative approach—comfortable navigating ambiguity and change.Excellent communication skills, able to translate complex technical concepts for diverse audiences.Experience building scalable solutions that integrate with broader systems and frameworks.Self-driven, curious attitude—you\'re always looking for smarter ways to solve tough problems.Bonus Points
Hands-on experience with optimization models (e.g., classification, regression, forecasting) for both deterministic and stochastic use cases.Background in machine learning.Familiarity with Streamlit and AI tools.#J-18808-Ljbffr