Customer Success Manager
Serve as strategic partner to enterprise clients in FinTech, Banking, and E-commerce, driving ROI from DataVisor's AI-powered fraud detection and AML SaaS platform through performance monitoring, best practices guidance, and cross-functional advocacy.
About the job
Responsibilities
- Act as the primary point of contact and trusted advisor for assigned enterprise customers, ensuring successful onboarding, adoption, and long-term value realization.
- Understand client business models, fraud/AML risk exposure, and operational needs to define success criteria and shape tailored solution strategies.
- Partner closely with clients to align our fraud detection and AML platform capabilities to their goals, driving measurable improvements in fraud prevention, loss reduction, and operational efficiency.
- Coordinate with internal teams (including Modeling, Product, and Engineering) to ensure timely delivery of enhancements, issue resolution, and optimization of detection outcomes.
- Translate customer insights into actionable feedback for internal roadmap planning and product improvements.
- Monitor detection performance metrics, support quarterly business reviews, and proactively identify opportunities for expansion or deeper integration.
- Educate clients on best practices in fraud/AML strategies and platform usage to maximize return on investment.
- Represent the voice of the customer internally and the voice of our platform externally, including participation in industry events, customer workshops, and solution showcases.
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
Skills
Fraud Strategy, AML, SQL, Python, Risk Analytics, Machine Learning, Rule Engines, Customer Success
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