Role overview
- Prototype and productionize new models and approaches to model customer behavior, with focus on long term impact of consumer actions and experiences by using Uber's planet scale data.
- Derive clear and actionable insights from your models and analyses, and communicate them to your stakeholders and business leaders to shape business strategy.
- Incorporate models in the broader framework of algorithmic decision making at Uber, influencing millions of outcomes and impacting the lives of millions of Uber users everyday. Collaborate with cross-functional teams such as product, engineering and operations to drive system development end-to-end from conceptualization to final product.
Basic qualifications
- M.S., or Bachelor's degree in Economics, Operations Research, or a related quantitative field (e.g., Statistics, Applied Mathematics, Computer Science with a strong modeling focus).
- Mininum 4 years of relevant industry experience as a Data Scientist, Applied Scientist, or equivalent (Mininum 2 years if holding a Ph.D.).
- Strong foundations in causal inference, experimental design and econometrics.
- Excellent analytical skills, with experience extracting user behavior insights from large datasets.
- Knowledge of underlying mathematical foundations of statistics, optimization and economics.
- Proficiency with Python for exploratory data analysis and modeling, and modern ML tools such as pytorch, tensorflow etc. Strong ability to communicate with technical and nontechnical audiences.
Preferred qualifications
- Mininum 5 years of relevant industry experience as a Data Scientist, Applied Scientist, or equivalent.
- PhD in quantitative fields such as Statistics, Economics, OR, Engineering, Physics, etc.
- Proficiency in Python and the modern model development frameworks such as pytorch etc.
- Experience in LTV (Life Time Value) modeling, causal inference from observational data and choice modeling.
- Experienced in using AI to hypercharge productivity and delivering 10x impact. Exceptional communication skills across technical, non-technical, and executive audiences.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Machine Learning Data Science Ai