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Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.
Amazon has built a reputation for excellence with recent examples of being named the #1 most trusted company for customers. To deliver on this reputation for trust, the Seller Partner Abuse team is tasked with identifying and preventing abuse for our customers and brand owners worldwide.
This team is seeking an innovative, results-oriented, customer-centric data scientist to drive expansion of innovative ML products globally in the 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.
- Use predictive analytics and machine learning techniques to solve complex problems and drive business decisions.
- Employ the appropriate algorithms to discover patterns of risks, and prevent abuse
- Design experiments, test hypotheses, and build actionable models to optimize SPA policies and operations
- Solve analytical problems, and effectively communicate methodologies and results both in writing and verbal
- Build predict models to forecast risks for product launches and help predict workflow and capacity requirements for SPA
- 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
- 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
- 2+ years working as a Data Scientist
- 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)
- 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 committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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