Senior Applied Scientist, Amazon Leo Data Science Platform

Amazon Inc.; Redmond (WA); On-site; USD 167,100 - 226,100; Full time

Benefits offered by this job

Sign-on payments

Restricted stock units

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking a Senior Applied Scientist for the Amazon Leo Data Science Platform in Redmond, Washington. This role involves leading data science initiatives to enhance fraud detection and improve customer experience. With at least 3 years of experience in building machine learning models, candidates must also possess a Ph.D. or Master’s and proficiency in Java, C++, or Python.

The position offers a competitive salary range of $167,100 – $226,100 annually, along with sign-on payments and comprehensive benefits including health insurance and parental leave.

Qualifications

• 3+ years of building machine learning models for business applications.
• Experience with neural deep learning methods and standard machine learning.
• Experience using modeling tools like R, TensorFlow, and Spark.

Responsibilities

• Lead end‑to‑end data science projects, including data extraction, model building, evaluation, and production deployment.
• Collaborate with teams to identify and address fraud vulnerabilities.
• Develop rules and machine learning models to prevent Customer Terminal usage fraud.

Skills

Machine learning model building

Programming (Java, C++, Python)

Neural deep learning methods

Data extraction and evaluation

Large-scale distributed systems

Education

Ph.D. or Master’s degree with applied research experience

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Job description

Senior Applied Scientist, Amazon Leo Data Science Platform

Amazon Leo is Amazon's low Earth orbit satellite network that delivers fast, reliable internet connectivity beyond the reach of existing networks. The Senior Applied Scientist will lead data science initiatives to improve fraud detection and customer experience monitoring, building scalable machine learning solutions and deploying them into production systems.

Export Control

Candidates must meet U.S. citizenship or permanent resident requirements per export control laws.

Key Responsibilities

• Lead end‑to‑end data science projects, including data extraction, model building, evaluation, and production deployment.
• Collaborate with fraud operations, engineering teams, and data platform staff to identify and address fraud vulnerabilities.
• Develop rules and machine learning models to prevent Customer Terminal usage fraud and abuse.
• Ensure solutions preserve and enhance user experience while reducing fraud risk.
• Communicate findings and recommendations with stakeholders at all levels.

Qualifications

• 3+ years of building machine learning models for business applications.
• Ph.D. or Master’s degree with 6+ years of applied research experience.
• Proficiency in programming languages such as Java, C++, Python or related.
• Experience with neural deep learning methods and standard machine learning.
• Experience using modeling tools like R, scikit‑learn, Spark MLLib, MxNet, TensorFlow, NumPy, SciPy.
• Experience with large‑scale distributed systems such as Hadoop and Spark.

Benefits

The base salary range for this position is $167,100.00 – $226,100.00 USD annually. The compensation package includes sign‑on payments, restricted stock units, health insurance, 401(k) matching, paid time off, and parental leave. For more details on benefits, visit Amazon's benefits page.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.