Uber
From Uber's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
About the role and team Working in Science at Uber means solving complex problems in a high-stakes, fast-moving environment.
Working in Science at Uber means solving complex problems in a high-stakes, fast-moving environment. You’ll turn massive amounts of unstructured data into focused plans of execution, navigating ambiguity to build technologies that directly influence every decision made in our marketplace. In this role, you’ll be the bridge between technical depth and business impact, solving messy, high-priority problems that don’t always have a textbook solution. You’ll thrive here if you possess an owner’s mindset, stay calm under pressure, and have the grit to drive projects through their entire lifecycle from idea inception to production.
Uber Direct is a B2B delivery-as-a-service product that leverages Uber's existing courier network to provide logistics capabilities to all kinds of businesses, from your favorite restaurant to major online retailers. The Direct science team builds the tech that enables smart decisions at every step of the product journey, combining product analytics, machine learning, algorithm design, and experimentation. We’re looking for someone who thinks critically and moves quickly, adapting the best tools for the moment to solve real-world transportation problems.
Develop data-driven business insights by collaborating across disciplines: product, engineering, and operations to identify growth opportunities and recommend prioritization of high-impact initiatives.
Build and scale statistical, optimization, and machine learning models that provide both strategic insights and real-time production enhancements to global products.
Design and analyze complex experiments using A/B testing and causal inference to provide results that drive critical decision-making.
Unblock technical barriers by driving the creation of logging, metrics, and diagnostic tools that orient teams around data-driven product development.
Define how teams measure success by developing robust metrics in close partnership with cross-functional stakeholders to align on long-term impact.
Lead through influence by effectively communicating complex technical findings and outcomes to leadership and technical partners.
Ph.D., M.S. or Bachelor's degree in Statistics, Machine Learning, Operations Research, Economics, Mathematics, Computer Science, or other quantitative fields.
5+ years of industry experience as an Applied or Data Scientist or equivalent (or 3+ years with a Ph.D.).
Proficiency in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl).
Experience designing experiments and interpreting results across a variety of key performance indicators.
Ph.D. degree in a quantitative field such as Machine Learning, Operations Research, Economics, or Statistics.
Outstanding communication skills with a track record of influencing leadership and technical teams through storytelling and data-driven insights.
Experience leading high-complexity technical projects and substantially influencing the scope and output of others.
Proven ability to work efficiently with large-scale datasets (e.g., 100M+ rows) using Spark, Hive, or HDFS.
Thought leadership to drive multi-functional projects from initial concept to production.
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 Seattle, WA-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.
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