The Operations Research/Decision Support team leads strategic projects/analyses to enable Box to achieve optimized decisions and business outcomes around new product design, product pricing, architecture changes, and infrastructure efficiency.
If these challenges excite you, come join an elite team of Capacity & Performance Engineers, Data Scientists, Hardware Engineers, and Operations professionals with alums from top companies (Andreesen Horowitz, Ebay, Twitter, McKinsey, etc)
We are looking for big thinkers and innovators to join us as a Senior/Staff Operations Research Engineer to tackle some of the most ambiguous, strategic problems facing the business today
Why the team needs you 
Our private & public multi-cloud architecture introduces exciting new challenges and layers of complexity. As Box scales, it is ever more critical to use data driven decision making to ensure we continue to optimize our business performance. We want to better understand our Infrastructure, what drives changes/growth, and make changes to optimize our revenue and cost structure at the most strategic level. 
Why you need Box 
This role will have the opportunity to work with almost every team at the company including C-level Execs, teams across Product, Software Development, Hardware Engineering, Datacenter Operations, Capacity Engineering, Pricing, Business Development & Partnerships, and more.  You'll be able to leverage your technical skills to produce complex mathematical models, deep-diving to discover important insights, and surfacing them to a variety of technical and non-technical audiences to drive changes in our business fundamentals and engineering roadmaps.
Who you are 
  • Degree in Statistics, Applied Mathematics, Operations Research, Computer Science, or a related quantitative field
  • You effectively collaborate with and communicate complex concepts to technical and non technical audiences at all levels, from C-Level to individual contributors
  • You have experience creating advanced models and are familiar with statistical methods applied to very large data sets (billions of records+)
  • You have experience building ETLs on Hive, Redshift
  • You are proficient  in Python, R, or a similar modeling language and in SQL
  • You bring clarity and insight to ambiguous problems and are tenacious in digging through quantitative and qualitative information
  • You are familiar with data visualization tools and methodologies
  • Working knowledge of technical infrastructure, distributed systems, and finance all preferred

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