Uber · New York, NY, United States
Skills: Python, Java
About the Role
Uber Marketplace is at the heart of Uber’s business, with Rider Pricing playing a critical role by setting prices and targeting promotions for Uber riders. Our team’s mission is to drive revenue growth, ridership growth and Uber’s profitability through advanced machine learning and data science. We build reliable, scalable platforms that optimize rider pricing in both real-time and offline systems, including baseline trip pricing and targeted discounts.
The Rider Pricing team is a fast-moving, high-opportunity space where you’ll have the chance to make a significant impact on the business. On this team, your work will affect over 95% of Uber’s mobility business revenue. You’ll work on the rider pricing optimization algorithms and systems, to build better pricing algorithms, optimization algorithms and models.
In this role, you'll apply advanced machine learning technologies, including deep learning, generative AI for causal modeling, representation learning and personalization, to optimize Uber’s pricing. You will also work with serving infrastructure and product teams to design and evolve the rider pricing systems to support new product and algorithm evolutions and drive Uber’s top-line rider and revenue growth.
What You’ll Do
Develop and implement machine learning and optimization solutions to solve critical business challenges, including rider pricing, discounts, promotion targeting, and personalized messaging. Build and scale models and systems for real-time and offline promotions, as well as rider pricing. Collaborate with cross-functional teams to ensure alignment and drive measurable business outcomes. Work on and have the opportunity to set technical directions for key ML, serving, and optimization system components that directly impact Uber’s growth.
Basic Qualifications
Bachelor’s degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 3+ years of full-time engineering experience. 2+ yea …truncated… ts, and deliver…
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