Offer summary

Qualifications:

5+ years of experience in fraud strategy, risk analytics, or customer success in fintech, banking, or e-commerce industries., Deep understanding of fraud/AML use cases and experience with machine learning-based detection systems., Strong analytical skills with proficiency in SQL and experience in Python or R for data analysis., Bachelor’s degree in a technical, analytical, or business-related field; advanced degree is a plus..

Key responsabilities:

Act as the primary point of contact and trusted advisor for enterprise customers, ensuring successful onboarding and long-term value realization.

Understand client business models and operational needs to define success criteria and shape tailored solution strategies.

Coordinate with internal teams to ensure timely delivery of enhancements and optimization of detection outcomes.

Educate clients on best practices in fraud/AML strategies and represent the voice of the customer internally and externally.

Job description

DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

As a Senior 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 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.

Job Location:

This is a remote-based position and can be located in the U.S. or Canada, preferably in the Eastern Time Zone.

Key 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

5+ 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

Bonus, Stock options, Retirement Plan, Health Insurance

Required profile