paid / full-time /
DESCRIPTION
We are growing and taking on more to make the world safe for ecommerce. Amazon.com's Buyer Risk Prevention (BRP) team is a centralized technology team that protect all of Amazon’s businesses and services from fraud and abuse. These systems, invisible to the customer, work seamlessly across the billions of transactions occurring simultaneously around the world. We are pioneering new techniques to detect and neutralize bad actors that attempt to abuse our policies.
BRP designs and builds high performance software systems using machine learning to identify and prevent abusive transactions. Abuse prevention is a real money game where our software teams strive to outsmart those who attempt to defraud Amazon and our customers. Come build with us! Every dollar of abuse that we prevent is a dollar of profit for Amazon or its 3P Sellers, a dollar that could be reinvested to deliver new features for our customers. Because of Amazon's huge scale, this a great opportunity to add hundreds of millions to the bottom line.
BRP is seeking an innovative, results-oriented, customer-centric data scientist to drive expansion of innovative ML products globally in the Policy Risk space.
As a Data Scientist, you will be responsible for modeling complex problems, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques. You will need to collaborate effectively with internal stakeholders and cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. The candidate should be able to apply a breadth of tools, data sources and analytical techniques to answer a wide range of high-impact business questions and present the insights in concise and effective manner. Additionally, the candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business.
Responsibilities:
- Use predictive analytics and machine learning techniques to solve complex problems and drive business decisions.
- Employ the appropriate algorithms to discover patterns of risks, abuse and help reduce bad debt
- Design experiments, test hypotheses, and build actionable models to optimize BRP operations
- Solve analytical problems, and effectively communicate methodologies and results
- Build predict models to forecast risks for product launches and operations and help predict workflow and capacity requirements for BRP operations
- Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies
- Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area
BASIC QUALIFICATIONS
- Master’s Degree in any quantitative discipline such as Statistics, Mathematics, Quantitative Finance, computer science, or Operational Research
- 4+ years of experience working in Analytics / Business Intelligence environment
- 4+ years professional experience in modeling and statistical analysis of large data sets
- Proven experience in working with databases and SQL in a business environment
- Demonstrated use of analytical packages and query languages such as SAS, SPSS and SQL
- Proven experience in design and execution of analytical projects
- Demonstrated experience working in large scale data bases and data warehouses
- Track record of developing and implementing models using programming and scripting (Java, Python, R, Ruby, C/C++, or Matlab)
PREFERRED QUALIFICATIONS
- Experience/knowledge of advanced machine learning techniques such as GBM, random forest, etc.
- Experience in e-commerce / on-line companies in fraud / risk control functions
- Coding skills in one of the modern languages Java, Python, Scala, R
- Experience with visualization technologies such as Tableau
- Experience in statistical techniques such as classification, clustering, regression, statistical inference, collaborative filtering, and natural language processing, experimental design, social networking analysis, feature engineering, etc.
- Compelling communication and influencing skills and participation in winning the support of management and influence the course of major strategic decisions
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation