Staff Applied Scientist - Capacity & Efficiency Engineering
UberAbout The Role
The Capacity & Efficiency Engineering (CEE) organization at Uber is seeking a Staff Data Scientist to join our team in Amsterdam. In this role, you will be responsible for designing and building forecasting models to better understand the growth drivers that require Uber's infrastructure to scale to meet product and business needs. You will also contribute to building a comprehensive understanding of Uber's resource consumption across its tech stack, identifying cost-saving opportunities, and developing simulation models to help Uber save significant resources in terms of money, time, and effort.
Key Responsibilities
- Develop forecasting models and iterate on model refinement to minimize forecasting errors by gaining a deeper understanding of how critical Uber infrastructure components scale.
- Derive insights from data to identify opportunities for efficiency and resource consumption reduction across the Uber infrastructure.
- Use statistical modeling techniques to develop northstar metrics and KPIs to provide a more rigorous data-driven approach to managing Uber infrastructure.
- Develop simulation models for the Uber infrastructure to improve understanding of various cost drivers and how to best control them, while managing risk, reliability, and availability.
- Conduct ad-hoc analysis, reporting, and build visualizations to communicate findings to Engineering Leadership.
- Present findings to senior leadership to drive business decisions.
Basic Qualifications
- 8+ years of experience as an applied scientist in the tech industry.
- Ph.D. or M.S. degree in Statistics, Economics, Mathematics, Machine Learning, Operations Research, or other quantitative fields, or equivalent industry experience.
- Knowledge of the mathematical foundations of statistics, machine learning, optimization, economics, and analytics.
- Advanced knowledge and experience in time-series forecasting, anomaly detection, and building ML models in production.
- Proficiency in Python and Apache Spark to work efficiently at scale with large data sets.
- Proficiency in libraries, languages, technologies, and tools like R, SQL, pandas, numpy, pyspark.
Preferred Qualifications
- Expertise with BI tools such as Tableau.
- Experience in algorithm development and prototyping.
- Exposure to the infrastructure domain, particularly capacity engineering.
- Exposure to financial analysis.
- Exposure to large-scale simulations.
Join us in Amsterdam and be part of a team that is at the forefront of driving efficiency and innovation in Uber's infrastructure. If you are passionate about data science and have a strong technical background, we would love to hear from you!
Benefits Extracted with AI
- Flexible work environment
- Opportunities for professional growth
- Collaborative team environment
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