Principal Product Manager , Forensic Analysis Products
Arlington, Virginia, USA
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Amazon’s Theft, Fraud, Abuse and Waste's (TFAW) mission is to identify and prevent erroneous and fraudulent payments to vendors, employees and carriers globally. TFAW uses advanced detection and prototyping methods for identifying anomalies in invoicing, payment, and other financial data. Investigators carry out complex investigations to ultimately prevent bad actors from receiving funds fraudulently. TFAW is fundamental to ensuring Amazon's Global Accounts Payable is able to deliver on its mission to pay vendors correctly and on time.
If you are excited about finding bad actors, building fraud analytics, developing forensic analysis products, risk management, strategic thinking and analytical skills, then this new and rare opportunity is for you! We are seeking a Principle Product Manager to develop our library of fraud rules across invoices, payments, vendors and other entities. The Principle will work with tech teams to build a library of analytics, using some of our existing fraud detection tools. This is a high impact role in fraud detection product development. You will be responsible for setting the strategic vision for our team's fraud library, enabling investigators and Risk Managers to detect and investigate more fraud quickly while minimizing false positives and thereby optimizing precision and recall. The successful candidate has experience developing products specific to finding bad actors, communicates flexibly to senior leaders, technical stakeholders, and customers. The successful candidate is adept at writing and influencing leaders towards a common product vision. You will play a significant role in driving the direction of how we use technology to scale decisions and expand into new fraud detection businesses, partnering with technology and science leaders across Finance Operations.
To be successful in this role, the leader will exhibit technical and functional skills needed to develop product while communicating business needs, excellent judgment and decision-making skills, high controllership mentality, strong analytical skills, ability to convert data into action, excellent communication skills including to senior leadership, and passion for operational excellence. A successful candidate thrives on autonomy and has a proven track record of influencing stakeholders at all levels.
Key job responsibilities
- Build a best-in-class rule-based fraud monitoring for payments and invoices to surface velocity and other trends not identified in upstream detection
- Partner with Product Managers - Tech and other tech roles to act on product roadmap
- Understand, at a deep level, how upstream invoicing systems impact fraud detection downstream
- Obsess over customers and investigators who are reviewing the output of rule-based analytics to ensure false positives are reduced
- Write persuasive narratives describing the product's vision including short term and long term plans
- Partner with prototyping team to ensure alignment across narrow use cases focused on specific areas of fraud versus a fraud library that focuses more generally on invoices and payments
- Bachelor's Degree in business, finance, data science or related field
- 10+ years' experience implementing and managing fraud risk analytics at scale
- 6+ years' experience in Product Management
- Excellent written and verbal communication
- MBA or Data Science graduate degree
- Experience in advanced anomaly detection using SQL, Python, or other coding language
- Proven track record of sound decision making, taking ownership, and delivering results in a leadership role.
- Track record of having earned the trust of leadership by challenging norms, upgrading team performance, enabling growth, and improving efficiency.
- Ability to dive deep into data, existing processes, people, and technology challenges in order to identify risks and opportunities.
- Interpersonal skills, including the written and oral communication skills necessary to build relationships and positively influence decision making.
- Demonstrated ability to meet deadlines while managing multiple complex projects.
- Demonstrated ability to lead through ambiguity & across large, complex and global corporate network, partnering & delivering effectively with other teams globally.
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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