Customer Success Manager – Fraud/AML Strategy

🔥 5 minutes ago

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Logo of DataVisor

DataVisor

51 - 200 employees

💸 Finance

💳 Fintech

☁️ SaaS

💰 Series C on 2019-10

Finance • Fintech • SaaS

DataVisor is an advanced fraud and risk management platform leveraging AI and machine learning to provide real-time solutions for financial institutions and other large organizations. The platform offers a comprehensive suite of tools to tackle various types of fraud, including account takeovers, application fraud, ACH and wire fraud, card fraud, and check fraud. DataVisor also provides solutions for AML (Anti-Money Laundering) compliance, helping banks, credit unions, fintech companies, and digital payment services detect and prevent fraudulent activity. Through its innovative machine learning algorithms and real-time data orchestration, DataVisor allows organizations to streamline their operations, reduce fraud losses, increase approval rates, and maintain compliance, all while protecting the integrity of their systems and user data. The company emphasizes quick and efficient integration with existing systems and provides educational resources to stay ahead of emerging threats, making it a valuable partner for modern financial operations.

📋 Description

• Serve as a strategic partner to key enterprise clients • Help drive ROI through advanced fraud detection and AML compliance • Lead customer engagements across Fortune 500 companies • Monitor detection system performance and advise best practices • Coordinate with internal teams to advocate customer needs • Translate customer insights into actionable feedback • Conduct business reviews and identify expansion opportunities • Educate clients on best practices in fraud/AML strategies

🎯 Requirements

• 3+ years of experience in fraud strategy, risk analytics, customer success, or fraud operations within fintech, banking, payments, or e-commerce industries • Deep understanding of fraud/AML use cases such as transaction fraud, account takeover, promotion abuse, synthetic identity fraud, or mule detection • Experience working with machine learning-based detection systems and/or rule engines for fraud prevention • Strong analytical skills; proficient with SQL, and experience in Python or R for data exploration and investigation • Excellent verbal and written communication skills; able to explain technical concepts to both technical and non-technical stakeholders • Confident in leading customer-facing discussions and executive presentations • Highly organized with strong project ownership and time management skills; able to manage multiple enterprise accounts simultaneously • Bachelor’s degree in a technical, analytical, or business-related field; advanced degree a plus

🏖️ Benefits

• Base salary • bonus & PTO

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