Base Salary
$202k - $224k/yr
Responsibilities
- Own the full lifecycle of targeting and personalization models, including problem framing, data preparation, training, offline evaluation, online experimentation, deployment, monitoring, and retraining.
- Build heterogeneous treatment effect models to estimate the incremental impact of interventions on users.
- Design budget-constrained allocation systems that account for incentive budgets, contribution targets, cannibalization, and surface frequency caps.
- Build personalized ranking and sequencing models for membership messaging across Uber Eats and Mobility apps.
- Partner with backend and platform engineers to productionize models in real-time serving paths and batch pipelines.
- Collaborate across Product, Engineering, Data Science, Finance, and Marketing to define concrete ML solutions for ambiguous business goals.
Requirements
- Bachelor’s degree in Computer Science, Statistics, Economics, Operations Research, or a related quantitative field, or equivalent practical experience.
- At least 5 years of experience building and shipping production ML models that drive product or business decisions.
- Strong proficiency in Python and modern ML frameworks, including PyTorch, scikit-learn, XGBoost, or LightGBM.
- Strong SQL skills and hands-on experience with large-scale data processing using Spark, Hive, Presto, or comparable technologies.
- Experience with experimental design and analysis, including A/B testing, power analysis, variance reduction, and interpreting noisy results.
- Experience taking models from notebooks through production pipelines, serving, monitoring, retraining, and deployment.
- Ability to explain modeling decisions and their business consequences to technical and non-technical audiences.
- Preferred experience with MLP-based uplift estimation, constrained optimization for resource allocation, incentive or pricing targeting, contextual bandits or reinforcement learning, subscription analytics, and technical leadership across ambiguous cross-functional scopes.
Benefits
- Eligible to participate in Uber’s bonus program.
- May be offered an equity award and other types of compensation.
- Eligible for a 401(k) plan and various benefits.
- Role is based in San Francisco, California.
Tech Stack
Categories
About Uber
We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything and earn their way. Movement is what we power. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real time. At the incredible speed of now. The idea for Uber was born on a snowy night in Paris in 2008, and ever since then our DNA of reimagination and reinvention carries on. We’ve grown into a global platform powering flexible earnings and the movement of people and things in ever expanding ways. We’ve gone from connecting rides on 4 wheels to 2 wheels to 18-wheel freight deliveries. From takeout meals to daily essentials to prescription drugs to just about anything you need at any time and earning your way. From drivers with background checks to real-time verification, safety is a top priority every single day. At Uber, the pursuit of reimagination is never finished, never stops, and is always just beginning.