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Senior Applied Scientist, Amazon Leo Data Science Platform

Amazon is hiring a Senior Applied Scientist, Amazon Leo Data Science Platform. It pays $167k-$226k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

  • On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
  • Pay on this posting starts in line with the typical applied scientist posting on Level.
  • The posting mentions TensorFlow, scikit-learn and Python among its tools and skills.
  • Level classes it as a senior role.
  • Amazon has 20,000+ other open roles on Level.

AI in this role

Lead machine learning initiatives to build, evaluate, and productionize models for fraud detection and customer experience monitoring in Project Leo.

TensorFlowscikit-learnPythonSQLMachine Learning Frameworks
machine-learningstatistical-modelingfraud-detectiondata-scienceproductionalization
Amazon Leo is Amazon's low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity.

The Role
As a Senior Applied Scientist in Project Leo, 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
As part of the Amazon Leo 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
The Amazon Leo Data Science Platform team builds services to ingest, transform, and aggregate data from various devices in Leo 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

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.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.



USA, WA, Redmond - 167,100.00 - 226,100.00 USD annually

How we rate this

Senior Applied Scientist, Amazon Leo Data Science Platform at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningStatistical ModelingFraud DetectionData ScienceProductionalizationTensorFlowscikit-learnPython

Also common in applied scientist jobs at this level

Pay

This job starts at
$167k
Typical applied scientist job
$167k

This posting starts close to the typical applied scientist job. See applied scientist jobs

Questions you could be asked

  1. Tell me about a project where machine learning was part of your work. What did you do?
  2. Tell me about a project where statistical modeling was part of your work. What did you do?
  3. Tell me about a project where fraud detection was part of your work. What did you do?
  4. Tell me about a project where data science was part of your work. What did you do?
  5. Tell me about a project where productionalization was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Machine learning, Statistical Modeling, Fraud Detection, Data Science, and Productionalization. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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