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Aml Risk Manager Jobs in Santa Clara, CA (NOW HIRING)

Collaborate with Operations, BSA/AML, Risk & Compliance, Treasury Management, IT, and frontline teams to support fraud detection, response, and prevention efforts * Provide fraudrelated guidance and ...

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Aml Risk Manager information

See Santa Clara, CA salary details

$60.5K

$131K

$199.7K

How much do aml risk manager jobs pay per year?

As of Sep 1, 2026, the average yearly pay for aml risk manager in Santa Clara, CA is $131,016.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,700.00 and $151,500.00 per year, depending on experience, location, and employer.

What is the difference between Aml Risk Manager vs Compliance Analyst?

AspectAml Risk ManagerCompliance Analyst
CertificationsCAMs, CRCM, or equivalentCAMs, CRCM, or equivalent
Work EnvironmentFinancial institutions, banks, or fintechsFinancial institutions, banks, or fintechs
Primary FocusIdentifying and managing AML risks, developing risk mitigation strategiesMonitoring compliance with regulations, conducting audits, and reporting

The Aml Risk Manager and Compliance Analyst roles often overlap in credentials and work environment, but the Aml Risk Manager primarily focuses on assessing and managing AML risks, while the Compliance Analyst concentrates on ensuring adherence to compliance standards and regulations. Both roles are essential in financial institutions to prevent financial crimes and ensure regulatory compliance.

Is AML risk management a lucrative career?

AML risk management is considered a well-paying career within the financial and compliance sectors, with salaries often increasing with experience, certifications, and responsibility level. Professionals in this field typically require knowledge of regulations, risk assessment, and compliance tools, and can advance to senior or managerial roles that offer higher compensation.
Infographic showing various Aml Risk Manager job openings in Santa Clara, CA as of August 2026, with employment types broken down into 85% Full Time, 13% Part Time, 1% Temporary, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $131,016 per year, or $63 per hour.

Customer Success Manager - Fraud/AML Strategy

DataVisor

Mountain View, CA • On-site

Other

PTO

This job post has expired today. Applications are no longer accepted.


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!

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