Uber Freight is looking to solve real-world logistics challenges through data-driven insights and innovation, leveraging advanced statistical modeling, machine learning, and causal inference.
Requirements
- Demonstrated proficiency in programming languages like Python or R for purposes of model development and analysis
- Proficiency in SQL for data manipulation and analysis
- Familiarity with statistical and machine learning methods such as regression, classification trees, unsupervised learning, causal inference, and time series analysis.
Responsibilities
- Collaborate with Data Scientists, Engineers, and internal stakeholders (Product, Engineering, Sales, Marketing, Finance, and Customer Success) to solve business problems using data.
- Apply statistical and machine learning techniques such as causal inference, recommender systems, and time series forecasting to generate insights or deploy models.
- Manage your own project end-to-end—from data exploration and analysis to presenting findings and/or deploying algorithms in a production environment.
- Contribute to internal data product improvements.
- Communicate results and recommendations clearly to technical and non-technical audiences.
Other
- Currently pursuing a Bachelors, Master’s, or PhD degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Physics, Economics, Operations Research, or Engineering).
- Expected graduation in Fall 2026 or Spring 2027.
- Strong problem-solving skills and ability to work in ambiguous environments.
- Collaborative mindset and eagerness to learn in a fast-paced, team-oriented setting.
- Travel requirements not specified, but role is Hybrid/On-site
