Senior Applied Scientist, Kuiper Data Science Platform

Redmond, Washington, USA

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Project Kuiper is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Project Kuiper will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity.

The Role
As a Senior Applied Scientist in AWS, you’ll be leading us in making critical and time sensitive decisions that impact customers. You’ll use your machine learning expertise to build solutions that can scale and solve the business problem, and your engineering experience to build systems that take those solutions to production; it's an exciting opportunity to apply data science to help improve fraud detection accuracy, inference, and customer experience monitoring activity. It’s fast paced, data driven, and impactful.

Export Control Requirement:
Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Key job responsibilities
The position requires hands-on expertise in Analytics to identify and isolate issues, Statistical Modeling and traditional Machine Learning, the ability to write queries to aid in data extraction, and the ability to productionalize models. This role is a self sufficient scientist that can source data, build and evaluate models, and ultimately take those models and rules to deployment. You should have excellent communication skills and be able to work with stakeholders at all levels. Above all you should be a passionate, hard-working and creative person who loves creating business impact, loves solving difficult problems and doesn’t mind getting involved in the details.

A day in the life
At Kuiper Data Science Platform team, you will collaborate with a diverse group of internal stakeholders, including fraud operations, Engineering teams, and the Data Platform, to identify and address fraud vulnerabilities. You will have the opportunity to develop rules and ML models to prevent Customer Terminal (CT) usage fraud and abuse. Your role will also allow you to leverage your customer-obsession skills by thoughtfully considering the user experience and ensuring it is not adversely affected by the mechanisms you design. If you are passionate about working with large-scale data, we offer ample opportunities to do so.

About the team
Kuiper Data Science Platform team build services to ingest, transform, and aggregate data from various devices in Kuiper Network, and auto detect, diagnose, and resolve issues. We use ML technology to monitor customer experience and prevent fraud and abuse.

Basic Qualifications


- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Ability to develop and deploy (in partnership with engineers) Machine Learning models that power specific applications

Preferred Qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Knowledge of AWS services such as EC2, Sagemaker

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t 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 $150,400/year in our lowest geographic market up to $260,000/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.

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Category: Data Science Jobs

Tags: AWS CX Deep Learning Distributed Systems EC2 Engineering Hadoop Java Machine Learning ML models MXNet NumPy PhD Python R Research SageMaker Scikit-learn SciPy Spark Statistical modeling Statistics TensorFlow

Perks/benefits: Career development Equity / stock options

Region: North America
Country: United States

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