Principal Applied Scientist, EC2 Optimization Science - Amazon

Description 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 decision-making algorithms to manage EC2's virtual and physical capacity systems. EC2 Capacity owns EC2's top-level customer satisfaction metric capacity availability and the forecasting & decision-making systems which drive significant capex investments in server ordering for AWS data centers. Optimization Science is a core team involved in the end-to-end design and implementation of various decision-making systems, which manage the trade-off 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 recognized background in mathematical optimization, including numerical solution of continuous and discrete problems using exact and and heuristic methods applied to very large-scale problems. Experience with decision-making under uncertainty; e.g., robust or stochastic optimization is an advantage. The candidate will apply their knowledge to match the end-customer 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 Principal Applied Scientist on the EC2 Optimization Science team, you are expected to be hands-on with both design, modeling, and implementation, leading junior scientists by example. You will review approaches by other scientists and engineers in terms of business relevance, technical validity, engineering / science interface, and computational performance. 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 documents that influence important investment and resource allocation decisions by clearly articulating the strategy, business impact, and technical challenges. Collaborating with other scientists, software engineers, and product managers you will develop creative, novel, and data-driven approaches to improve our existing cloud compute offerings and define new ones in a fast-paced and quickly changing environment, improving the experience of our customers and impacting the bottom line of EC2. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA Basic Qualifications - Ph.D. in Operations Research, Applied Mathematics, Computer Science, Statistics or a related field with publications in refereed academic journals. - At least 10 years of academic and / or industry experience after the PhD degree in solving large-scale optimization problems. - Track record of delivering analytical solutions with big (business) impact. - Excellent writing skills for presenting business cases and to document the models and analyses and present the results/conclusions in order to influence important decisions. - In-depth knowledge of exact, approximation algorithms, and heuristic methods for solving difficult optimization problems like resource allocation, vehicle routing, network design. - In-depth 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 high-level modeling languages (e.g., AMPL, Mosel, R, Matlab). - Experience in prototyping and developing software in traditional programming languages (e.g., C++, Java, Python, Julia). - Familiarity with SQL and experience with very large-scale data. The ability to manipulate data by writing scripts (Python, Perl, Ruby) is a plus. - Statistical analysis, machine learning and data-modeling in a database environment are a plus. Preferred Qualifications Professional traits that are not unique to this position, but necessary for Amazon leaders: - Exhibits excellent judgment - Has relentlessly high standards - Thinks strategically, but stays on top of tactical execution - Expects and requires innovation of her/his team - Thinks big and has convictions - Result-oriented - Has the innate ability to inspire passion in others - Previous work with cloud computing, a passion for technology. 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $159,100/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on 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.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.