DataVisor

Customer Success Manager - Fraud/AML Strategy

DataVisor$100K — $130K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years in fraud strategy, risk analytics, or customer success within fintech, banking, payments, or e-commerce.
  • Deep understanding of various fraud/AML use cases, including transaction fraud and account takeover.
  • Familiar with machine learning detection systems and rule engines for fraud prevention.
  • Strong analytical skills with knowledge of SQL; experience in Python or R is a plus.
  • Excellent communication skills; capable of translating technical concepts for diverse audiences.
  • Confident in leading discussions and presentations for clients.
  • Highly organized; capable of managing multiple enterprise accounts simultaneously.
  • Bachelor's degree in a relevant field; advanced degree is a plus.

Responsibilities

  • Act as the main contact and trusted advisor for enterprise customers.
  • Understand client businesses to define success criteria and tailored solutions.
  • Align fraud detection and AML platform capabilities with client goals.
  • Work with internal teams to ensure timely delivery and optimization of solutions.
  • Translate client insights into actionable feedback for product improvements.
  • Monitor performance metrics and identify expansion opportunities.
  • Educate clients on best practices in fraud and AML strategies and platform use.
  • Represent customer interests internally and at industry events.

Benefits

  • Base salary, bonus, and paid time off (PTO).
Full Job Description
Job Summary

As a Customer Success Manager (CSM), you will serve as a strategic partner to key enterprise clients, helping them drive ROI through advanced fraud detection, AML compliance, and operational optimization. You'll lead customer engagements across a portfolio of Fortune 500 companies in FinTech, Banking, and E-commerce, providing expert guidance on how to maximize value from our industry-leading SaaS platform.

Your responsibilities include monitoring detection system performance, advising on best practices for using machine learning models, rules engine, and device intelligence signals, and identifying opportunities to reduce fraud or money laundering risks and streamline operations. You'll work cross-functionally with Product and Engineering teams to advocate for customer needs and support ongoing innovation.

This role combines strategic consulting, data-driven decisioning, and hands-on product expertise to deliver measurable impact for our clients.

Requirements
  • 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


Skillset 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

About DataVisor

DataVisor is an artificial intelligence company that provides fraud detection and prevention solutions for financial services, e-commerce, and social platforms. The company was founded in 2013 and is headquartered in Santa Clara, California. DataVisor uses machine learning algorithms to analyze large amounts of data and detect fraudulent activities in real-time. The company's solutions can help businesses reduce fraud losses, improve customer experience, and increase operational efficiency. DataVisor has partnerships with major financial institutions and e-commerce companies and is backed by several venture capital firms.
Learn more about DataVisor
Size
200 employees
Industry
Founded
2013

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