Business Analyst - Fraud Prevention

Recruiter
Amazon
Location
Hyderabad, Andhra Pradesh, India
Salary
Competitive salary
Posted
10 Jun 2021
Closes
12 Jun 2021
Ref
1496582
Job role
Business analyst, CFO
Description:
Amazon is seeking dedicated, hardworking, analytical candidates with a proven track record of performance and results-oriented thinking to join our Accounts Payable (AP) Fraud Prevention team. Our ideal candidate thrives in a fast-paced environment, relishes working with large transactional volumes and big data, and is passionate about data analysis.

As a Business Analyst for Fraud Prevention you will be eager to translate data into actionable insights for business teams and key stakeholders. You will identify areas of opportunity to automate and scale ad-hoc analyses. You will enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format. You will also partner with business teams and key stakeholders to create key performance indicators and new methodologies for measurement.

This role requires an individual who can take ownership, has excellent analytical abilities, and the ability to work with technology, finance, and business teams. The position relies on analytical and problem solving skills, including the ability to recognize non-obvious patterns, analyze diverse data sets and work closely with internal teams and stakeholders to recommend solutions in an ambiguous environment.
• Build dashboards for metrics, key performance indicators and other reporting needs

• Own metrics reporting for Travel Expense Reimbursement Audit team within AP Fraud Prevention

• Analyze data from diverse data sources to identify fraud trends and proactively take action to improve efficiency and reduce time to identify new fraud techniques, tactics and procedures.

• Analyze fraud data to determine patterns on fraud activity

• Monitor evolving fraud clusters and propose new rule criteria using SQL

• Analyze rule performance trends

• Report on daily fraud trends and cluster characteristics

• Work with internal teams to come up with action plans to address corrective and preventative measures to mitigate risk

• Work with stakeholders to drive process improvements that will impact internal and external customers

• Contribute and/or lead special projects which reduce fraud related losses, while maintaining focus on a positive customer experience

• Work with cross-functional teams across Amazon to collaborate on fraud risks and investigations

• Communicate analytical insights to key fraud stakeholders

Basic Qualifications:
• 4+ year of relevant experience in data analysis
• 1+ years of experience in extracting and processing data using SQL and Excel
• 1+ years of experience with Data Mining

Preferred Qualifications:
• Experience in Accounts Payable, Risk, or other relevant field
• Proficiency in forensic data analysis, data modeling and/or data mining techniques to detect patterns of fraud
• Proven ability to make decisions in a timely manner with incomplete or ambiguous information
• Demonstrated ability to effectively manage time and individually prioritize multiple tasks of competing priority
• Excellent oral/written communication and presentation skills, including an ability to effectively communicate with both internal and external stakeholders
• Ability to operate at both a granular and macro level
• Demonstrate excellent judgment, discretion, composure, and professional attitude
• Fast learner who seeks out and generously shares best practices
• Excellent team player capable of learning and sharing knowledge in a global team environment

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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