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About the role and team
Science and Engineering at Uber mean building for real-world impact under real-world constraints. As a Senior Applied Scientist, you will work at the high-stakes intersection of economics, statistics, and computer science to build the intelligent systems that power our global marketplaces. Unlike purely analytics roles, this is a production-focused position where you will turn "messy" behavioral data into scalable, machine-readable insights and automated decision-making engines.
You will join a high-stakes environment where the work is fast-moving, and the systems you build directly affect how millions of people and things move across our global platforms every single day. Collaborating closely with Product and Engineering, you will lead high-visibility projects from conceptualization to global productionization, navigating technical debt and shifting priorities along the way. If you are a systems-thinker who stays calm under pressure and is motivated to build production-grade models that solve unstructured problems without a textbook solution, this is where you’ll grow.
What you’ll do
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Build and deploy production-grade ML models and statistical algorithms that enhance platform intelligence and user experience in real-time environments.
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Design complex experiments and causal inference frameworks to interpret results and drive trade-offs between short-term wins and long-term system reliability.
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Architect underlying systems, observability platforms, and automated tooling required to monitor model performance and detect degradations at scale.
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Solve high-impact problems by translating ambiguous business needs into rigorous mathematical frameworks and production-ready code.
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Collaborate across Engineering, Product, and Operations to influence technical roadmaps and drive the adoption of scientific best practices.
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Own your work end-to-end, from identifying raw features and handling data imbalance to debugging production issues when the stakes are high.
Basic Qualifications
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Minimum 4 years of professional experience as a Machine Learning Scientist, Research Scientist, or Applied Scientist with a record of scoping complex problems independently.
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Expert proficiency in probability and statistics (e.g., multivariate distributions, sampling) and core optimization techniques (e.g., Gradient Descent, MCMC).
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Advanced coding proficiency with the ability to contribute to production-level codebases and develop modular tools re-used across teams.
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Experience performing extensive testing, monitoring, and instrumenting alerting to ensure the reliability of real-time systems.
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Demonstrated business acumen with the ability to justify technical decisions within a broader strategic business case.
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Exceptional communication skills with the ability to produce high-impact material for senior audiences and manage meetings with clear objectives.
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M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, Economics, or another quantitative field (or equivalent professional experience).
Preferred Qualifications
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Deep domain expertise in developing large-scale intelligent systems that manage supply, demand, or user behavior in a dynamic environment.
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Experience with Bayesian methods, probabilistic programming (e.g., STAN or Pyro), or advanced reinforcement learning.
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Demonstrated ability to lead multi-functional projects and navigate extreme ambiguity in a self-guided manner.
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Grit and a strong sense of ownership, with the ability to deliver on tight timelines while maintaining a high bar for engineering excellence.
For New York City, NY-based roles: The base salary range for this role is USD $190,000 per year - USD $211,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $190,000 per year - USD $211,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.