Uber - San Francisco, CA
posted about 1 month ago
The Investment Modeling Team at Uber is at the forefront of driving the company's global incentive and pricing strategies across all pricing and incentive mechanisms and cities worldwide! Encompassing both Mobility and Delivery businesses, we help Uber hit more aggressive growth and profitability targets while maintaining the overall health of the marketplace. We pursue this objective via an ML-driven algorithmic approach, using state-of-the-art Machine Learning (ML) and Optimization techniques to learn from massive datasets Uber has, estimate the composite marketplace pricing and incentive impact under various conditions, and identify the optimal investment strategy! To support and facilitate this work, we have also developed our in-house ML and optimization infrastructure, including data ETL, feature store, dev & viz tooling, model training, serving, storage and backtest solutions. We extensively use the latest technologies and libraries, such as HDFS, Spark, Ray, PyTorch, Horovod, Modin, etc, in our systems. We are actively seeking individuals who excel in problem-solving and critical thinking, are proficient in coding, with proven track records of learning and growth, and have prior experience in ML model, feature, and infrastructure development. Join us in our pursuit of excellence as we continue to shape the future of Uber's global incentive and pricing strategies through innovative engineering and model-driven insights.