Senior Applied Scientist EC2 Optimization Science

AWS Elastic Compute Cloud (EC2 Capacity Org is looking for an experienced applied optimization expert. This leader will join the Optimization Science Team to design implement and scale decisionmaking algorithms to manage EC2s virtual and physical capacity systems.

EC2 Capacity owns EC2s toplevel customer satisfaction metric capacity availability and the forecasting & decisionmaking systems which drive significant capex investments in server ordering for AWS data centers. Optimization Science is a core team involved in the endtoend design and implementation of various decisionmaking systems which manage the tradeoff between capex and capacity availability while matching demand and supply at different planning horizons. The stakeholders and partners include engineering and product management orgs within EC2 as well as the AWS Infrastructure Supply Chain (AIS) organization.

We are seeking an expert with a strong background in mathematical optimization with excellent modeling skills and expertise in the numerical solution of continuous and discrete problems using exact and and heuristic methods applied to very largescale problems. Experience with decisionmaking under uncertainty; e.g. robust or stochastic optimization is an advantage. The candidate will apply their knowledge to match the endcustomer demand for virtual machines to physical resource supply at horizons ranging from five minutes to 13 years. The variety of problems requires principled mathematical decomposition and a good interface design between inputs and outputs at various horizons. Navigating the ambiguity of design choices across horizons is a critical component of the role. In a typical project we analyze large volumes of data and then develop a prescriptive optimization model with inputs from ML or statistical models and business users. Our solution approaches are validated through simulations and / or production A/B tests. Being successful requires having the scientific breadth to understand the interactions between different phases of a project from data analysis through to production including resolving issues after rollout.

As a Senior Applied Scientist on the EC2 Optimization Science team you are critical to the speed and excellence of the endtoend deliveries of production systems with optimizationbased analytical engines. You will be handson with the mathematical modeling and implementation and will also contribute to the design of the engineering system with the scalability extensibility maintainability and correctness of the optimization engine in mind.

You will review approaches by other scientists and engineers in terms of business relevance technical validity engineering / science interface and computational performance. You will mentor and lead junior scientists by example. Communicating your results to guide the direction of the business and working with software development teams to implement your ideas in code is key to success. You will write technical and less frequently business documents that influence engineering investments and business direction. Collaborating with other scientists software engineers and product managers you will develop creative novel and datadriven approaches to improve our existing cloud compute offerings and define new ones in a fastpaced and quickly changing environment improving the experience of our customers and impacting the bottom line of EC2.

**Basic Qualifications**
PhD in Operations Research Applied Mathematics Computer Science Statistics or a related field. A PhD can be replaced by a masters degree in the same fields and four years of relevant academic and / or industry research experience.
At least 3 years of academic and / or industry experience after the PhD degree in solving largescale optimization problems.
Track record of delivering analytical solutions with business impact.
Indepth knowledge of exact approximation algorithms and heuristic methods for solving difficult optimization problems like resource allocation vehicle routing network design.
Indepth knowledge of continuous and discrete optimization methods accompanied by associated expertise in the use of tools and the latest technology (e.g. CPLEX Gurobi XPRESS).
Ability to implement models and tools through the use of highlevel modeling languages (e.g. AMPL Mosel R Matlab).
Experience in prototyping and developing software in traditional programming languages (e.g. C Java Python Julia) using mathematical solver interfaces.
Familiarity with SQL and experience with very largescale data. The ability to manipulate data by writing scripts (Python Perl Ruby) is a plus.
Good writing skills to document the models and analyses and for presenting business cases with results/conclusions in order to influence important decisions.

**Preferred Qualifications**
These are not required but are a plus:
Knowledge and experience in statistical analysis and machine learning.
Publications in refereed academic journals.
Previous work in cloud computing.


About the team
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PhD in operations research applied mathematics theoretical computer science or equivalent or Masters degree and 7 years of building machine learning models or developing algorithms for business application experience

Statistical analysis
Machine learning

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race national origin gender gender identity sexual orientation protected veteran status disability age or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit https://amazon.jobs/content/en/howwehire/accommodations for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150400/year in our lowest geographic market up to $260000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit https://www.aboutamazon/workplace/employeebenefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.