DESCRIPTION
Job Description
Have you ever thought about what it takes to detect and prevent fraudulent activity among hundreds of millions of e-commerce transactions across the globe What would you do to increase trust in an online marketplace where millions of buyers and sellers transact How would you build systems that evolve over time to proactively identify and neutralize new and emerging fraud threats
Our mission in Payment Risk is to make Amazon the safest place to transact online. Payment Risk safeguards every financial transaction across all Amazon sites, while striving to ensure that these efforts are transparent to our legitimate customers. As such, Payment Risk designs and builds the software systems, risk models and operational processes that minimize risk and maximize trust in Amazon.com.
As a Business Analyst in Payment Risk Analytics, you will be responsible for analyzing terabytes of data to identify specific instances of risk, broader risk trends and points of customer friction, developing scalable solutions for prevention. You will work with team members to ensure that the volume being flagged for manual review aligns with available capacity and Service Level Agreements (SLA’s) are met. You will be responsible for building a robust set of operational and business metrics and will utilize metrics to determine improvement opportunities.
Responsibilities:
. Understand the various operations across Payment Risk
. Design and develop highly available dashboards and metrics using SQL and Excel/Tableau
. Understand the requirements of stakeholders and map them with the data sources/data warehouse
. Own the delivery and backup of periodic metrics, dashboards to the leadership team
. Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies
. Execute high priority (i.e. cross functional, high impact) projects to improve operations performance with the help of Operations Analytics managers
. Perform business analysis and data queries using appropriate tools
. Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area
. Execute analytical projects and understanding of analytical methods (like ANOVA, Distribution theory, regression, forecasting, Machine Learning Techniques, etc.)
BASIC QUALIFICATIONS
· 1+ years of experience in financial/business analysis
· Experience with SQL or ETL
· Experience defining requirements and using data and metrics to draw business insights
Knowledge & Skills/ Business Acumen/ Education & Experience
Basic qualifications
. Bachelor’s Degree in any quantitative discipline such as Statistics, Mathematics, Quantitative Finance or Operational Research
. At least 2 or 3 years of experience working in Analytics / Business Intelligence environment
. Experience in working with databases and SQL in a business environment
. Demonstrated use of analytical packages and query languages such as SQL, Python, R or SAS
. Prior experience in design and execution of analytical projects
. Worked extensively in large scale data bases and data warehouses
PREFERRED QUALIFICATIONS
Preferred qualifications
. Experience in e-commerce / on-line companies in fraud / risk control functions
. Analytical mindset and ability to see the big picture and influence others
. Experience with visualization technologies such as Tableau
. Detail-oriented and must have an aptitude for solving unstructured problems. The role will require the ability to extract data from various sources and to design/construct/execute complex analyses to finally come up with data/reports that help solve the business problem
. Strong oral, written and presentation skills combined with the ability to be part of group discussions and explaining complex solutions
. Ability to apply analytical, computer, statistical and quantitative problem solving skills is required
. Ability to work effectively in a multi-task, high volume environment
. Ability to be adaptable and flexible in responding to deadlines and workflow fluctuations
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