Advanced Risk Prevention Data Scientist

2 days ago


Hyderabad, Telangana, India myGwork Full time
Job Overview

We are seeking a highly skilled Advanced Risk Prevention Data Scientist to join our innovative team at Amazon. As a key member of the Buyer Risk Prevention (BRP) Machine Learning group, you will play a crucial role in developing advanced algorithmic systems that help manage safety of millions of transactions every day.

Estimated Salary: $145,000 - $180,000 per yearKey Responsibilities
  • Demonstrate expertise in supervised and unsupervised algorithms, including tree-based models, neural networks, and clustering techniques.
  • Rapidly design, prototype, and test multiple hypotheses in a high-ambiguity environment, utilizing quantitative analysis and business judgment.
  • Report findings in a scientifically rigorous manner, collaborating with software engineers, product managers, and domain experts to identify and address challenges requiring innovative solutions.
  • Acquire knowledge of Amazon's diverse data resources and determine when, how, and which resources to leverage or exclude.
  • Integrate successful experiments into large-scale, highly complex production services by collaborating with software engineering teams.
  • Maintain technical documentation and effectively communicate results to diverse audiences.
BASIC QUALIFICATIONS:

- 7+ years of experience as a data scientist or similar role

- 7+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab, etc.)

- Experience with statistical models, including multinomial logistic regression

- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

PREFERRED QUALIFICATIONS:

- Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)

- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

- Experience as a technical leader and mentor on a data science team



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