Uber Senior Infrastructure Demand Planner Amsterdam 

United States, West Virginia 

627401917

What you'll do

Furthermore, you'll

• Partner closely with platform, technology, and product teams to understand their growth, sources of demand, optimize growth models, identify demand forecasting risks and efficiency opportunities.
• Develop forecasting models and iterate on model refinement to minimize forecasting errors by developing a deeper understanding of how various 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 help provide a more rigorous data-driven approach to manage the Uber infrastructure.
• Develop simulation models for the Uber infrastructure to improve our understanding of the 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

• 4+ years of working experience in either capacity resource forecasting, demand planning, in the tech industry.
• B.S. degree in Computer Science, Statistics, Economics, Mathematics, Machine Learning, Operations Research, or other quantitative fields, or equivalent industry experience.
• Excellent communication skills and a track record of broad stakeholder engagement.
• Knowledge of underlying demand models, mathematical foundations of statistics, optimization, resource economics, and analytics.
• Knowledge and experience in time-series forecasting, anomaly detection and building demand models in production.
• Strong interpersonal skills and attention to detail.

Preferred Qualifications

• Expertise with BI tools such as Tableau.
• Exposure to the infrastructure domain, particularly capacity engineering.
• Exposure to financial analysis.
• Ability to use Python and Apache Spark to work efficiently at scale with large data sets.
• Proficiency in languages, technologies and tools like R, SQL, Spark, Hive.

* Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .