Sr Applied Scientist

Uber; New York (NY); On-site; USD 190,000 - 211,000; Full time

Benefits offered by this job

Bonus program

Equity

401(k) plan

Benefits

Job summary

Uber's Science and Engineering team seeks a Senior Applied Scientist to build production-grade ML models at the intersection of economics, statistics, and computer science, turning messy behavioral data into scalable, machine-readable insights and automated decision engines powering our global marketplaces.

You will collaborate with Product and Engineering, lead high-visibility projects from concept to production, design complex experiments, and ensure reliability of real-time systems while

Qualifications

• Minimum 4 years of professional experience as a Machine Learning Scientist, Research Scientist, or Applied Scientist with a record of scoping complex problems independently.
• Advanced coding proficiency for production-level codebases and modular tools.

Responsibilities

• Build and deploy production-grade ML models and statistical algorithms for real-time environments.
• Design complex experiments and causal inference frameworks to drive trade-offs between short-term wins and long-term system reliability.
• Architect underlying systems, observability platforms, and automated tooling to monitor model performance and detect degradations at scale.
• Collaborate with Engineering, Product, and Operations to influence roadmaps and adopt scientific best practices.
• Own end-to-end work from raw features to debugging production issues when stakes are high.

Skills

Production ML systems

Experiment design

Statistical inference

Strong communication

Independent problem scoping

Education

MS/PhD in CS/ML/Stats

Tools

Python

Stan/Pyro

MCMC

Bayesian methods

Job description

Cleaned Document

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

• Build and deploy production-grade ML models and statistical algorithms that enhance platform intelligence and user experience in real-time environments.
• Design complex experiments and causal inference frameworks to interpret results and drive trade-offs between short-term wins and long-term system reliability.
• Architect underlying systems, observability platforms, and automated tooling required to monitor model performance and detect degradations at scale.
• Solve high-impact problems by translating ambiguous business needs into rigorous mathematical frameworks and production-ready code.
• Collaborate across Engineering, Product, and Operations to influence technical roadmaps and drive the adoption of scientific best practices.
• 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

• Minimum 4 years of professional experience as a Machine Learning Scientist, Research Scientist, or Applied Scientist with a record of scoping complex problems independently.
• Expert proficiency in probability and statistics (e.g., multivariate distributions, sampling) and core optimization techniques (e.g., Gradient Descent, MCMC).
• Advanced coding proficiency with the ability to contribute to production-level codebases and develop modular tools re-used across teams.
• Experience performing extensive testing, monitoring, and instrumenting alerting to ensure the reliability of real-time systems.
• Demonstrated business acumen with the ability to justify technical decisions within a broader strategic business case.
• Exceptional communication skills with the ability to produce high-impact material for senior audiences and manage meetings with clear objectives.
• M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, Economics, or another quantitative field (or equivalent professional experience).

Preferred Qualifications

• Deep domain expertise in developing large-scale intelligent systems that manage supply, demand, or user behavior in a dynamic environment.
• Experience with Bayesian methods, probabilistic programming (e.g., STAN or Pyro), or advanced reinforcement learning.
• Demonstrated ability to lead multi-functional projects and navigate extreme ambiguity in a self-guided manner.
• 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.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.

Ready to Ride?

This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.