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Applied Scientist, CloudTune, CloudTune Forecasting

Job ID: 1774991 | Amazon.com Services LLC

DESCRIPTION

Job summary
Amazon's CloudTune group is looking for an experienced Applied Scientist to join our forecasting team. The team develops large-scale scale models to inform team-level budget allocations and procurement/allocation of compute capacity for Amazon businesses during new product launches, high velocity events and non-peak periods. This role will be contributing to a managed service that uses historical data and business signals to deliver time series forecasting for specialized use cases. The service combines a variety of distinct forecasting models, including neural networks, to produce highly accurate forecasts.

As a scientist in the CloudTune team you'll also partner with technology and business teams to build new services that surprise and delight our customers. We develop sophisticated algorithms that involve learning from large amounts of past data. These forecasts are used to determine the level of investment in capital expenditures, promotional activity, engineering efficiency projects and determining financial performance.

You will work on mathematical problems with a high level of ambiguity. You will analyze and process large amounts of data, develop new algorithms and improve existing approaches based on statistical models, machine learning algorithms and big data solutions to automatically scale Amazon’s compute infrastructure, optimizing the balance between availability risk and cost efficiency for all of Amazon businesses.

We are looking for top scientists capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. We're an agile team with significant impact. If you can think big and want to be a part of a fast moving team breaking new ground at Amazon.com, and you meet the qualifications, we would like to speak with you!

Key job responsibilities
· Process and analyze large data sets, mining additional data sources as needed
· Analyze compute scaling metrics to identify business drivers that influence infrastructure expenditures
· Build mathematical models to represent demand forecasting at various levels.
· Prototype these models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.
· Create, enhance, and maintain technical documentation, and present to other scientists and business leaders.

BASIC QUALIFICATIONS

· MSc. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· 4+ years of hands-on experience in predictive modeling and machine learning or equivalent PhD degree.
· Strong working knowledge of data cleaning, machine learning, and analytics techniques.
· Ability to distill problem definitions, models, and constraints from informal business requirements; and to deal with ambiguity and competing objectives
· Comfortable working in a fast paced, highly collaborative, dynamic work environment
· At least 2+ years hands on experience programming in Python, R, Java, C#, C++ or other similar programming languages
· Strong verbal and written communication, influencing and partnership skills
· Ability to convey rigorous mathematical concepts and considerations to non-experts

PREFERRED QUALIFICATIONS

· Significant peer reviewed scientific contributions in relevant field.
· Extensive experience applying theoretical models in an applied environment.
· Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar).
· Strong fundamentals in problem solving, algorithm design and complexity analysis.
· Strong personal interest in learning, researching, and creating new technologies with high commercial impact.


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.