Senior Applied Scientist , EC2 Optimization Science

Amazon • Seattle, WA

2d

About The Position

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 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 large-scale problems. Experience with decision-making under uncertainty;
e.g., robust or stochastic optimization is an advantage. Candidates at the OR/ML
interface, and particularly those who have experience applying ML / Gen AI
methods to enhance and improve optimization algorithms or optimization-based
decision-making systems, are encouraged to apply. 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 Senior Applied Scientist on the EC2 Optimization Science team, you are
critical to the speed and excellence of the end-to-end deliveries of production
systems with optimization-based analytical engines. You will be hands-on 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 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.

Requirements

• PhD in operations research, applied mathematics, theoretical computer science, or equivalent, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
• Knowledge of optimization mathematics such as linear programming and nonlinear optimization
• Knowledge of databases (querying and analyzing) such as SQL, MYSQL, and ETL Manager and working with large data sets
• 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).
• Experience in prototyping and developing software in traditional programming languages (e.g., C++, Java, Python, Julia) using mathematical solver interfaces.
• Good writing skills to document the models and analyses and for presenting business cases with results/conclusions in order to influence important decisions.

Nice To Haves

• Knowledge of quantitative data analysis and statistics
• Machine learning with applications to optimization
• Experience in decision-making under uncertainty; e.g., using robust or stochastic optimization.

Responsibilities

• hands-on with the mathematical modeling and implementation
• contribute to the design of the engineering system with the scalability, extensibility, maintainability, and correctness of the optimization engine in mind
• review approaches by other scientists and engineers in terms of business relevance, technical validity, engineering / science interface, and computational performance
• mentor and lead junior scientists by example
• Communicating your results to guide the direction of the business
• working with software development teams to implement your ideas in code
• 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 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.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree