L5 Applied Scientist

Job ID: 1547577 | Amazon.com Services LLC


The Operation Research Science Team in the Amazon Devices Demand Planning org is looking for an Applied Scientist with a background in Operations Research and Management Sciences. Our team is responsible for optimization algorithms which run world-wide supply chain which for the Amazon Devices business, which includes: tablets, eReaders, echo, Alexa, cameras, and other smart home appliances. We formulate and solve challenging large-scale optimization problems which ingest demand forecasts and produce optimal procurement, production, distribution, and inventory management plans. We are also responsible for the long-term build capacity planning, which involves deciding on: whether we should green-light products; the level of investment in capital expenditures; material resources, inventory levels; and overall financial performance. We also work closely with the demand forecasting, material procurement, production planning, finance, and logistics teams to optimize our inventory allocation in our worldwide channels given operational constraints.

A day in the life
The successful candidate will be a self-starter, with strong OR/Optimization research and implementation skills, comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment and a desire to help shape the overall business.

About the hiring group
(See elevator pitch for team description and mission.)

Job responsibilities
· Design and develop advanced mathematical, optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions in the areas of supply chain optimization, network flows, demand planning, inventory management and distribution.
· Apply mathematical optimization techniques (linear, quadratic, SOCP, robust, stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming, model predictive control) and algorithms to design optimal or near optimal strategies, to be used by in-house decision support tools and software.
· Research, prototype and experiment with these models by using modeling languages such as Python, MATLAB, Mosel or R; participate in the production level deployment.
· Influence organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists.
· Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans.
· Create, enhance, and maintain technical documentation, and present to other Scientists, Product, and Engineering teams.

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.

Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records


· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· 2+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
Please ignore the default Basic Qualifications above. The following are the actual Basic Qualifications for this role:
· PhD or equivalent Master's Degree plus 4+ years of experience in Operations Research, Industrial Engineering, Electrical Engineering, Computer Science, or optimization related field
· Expertise in optimization: linear, non-linear, mixed-integer, large-scale, network, robust, stochastic
· Expertise in building optimization models, systems modeling, and model predictive control (MPC)
· Experience with implementation using OR tools (e.g. Gurobi, CPLEX, XPRESS)
· Expertise in validating and simulating math optimization models
· Strong communication and documentation skills


· Exposure to statistical modeling, forecasting, and machine learning
· Experience designing and supporting large-scale optimization systems in a production environment
· Experience with large data sets, big data and analytics
· Proficiency in at least one modern programming language such as Python, Java or C++
· 1+ years of relevant development experience in Object-Oriented Design and Service Oriented Architecture