Data Analyst – AML & Financial Crime

Mastercard
Mexico City, MexicoPosted 3 April 2026

Tech Stack

Job Description

Our Purpose Mastercard powers economies and empowers people in 200 countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Analyst – AML & Financial Crime At Mastercard, we are committed to protecting our network from being used to facilitate money laundering or terrorist financing. The Global Anti-Money Laundering (AML) Financial Intelligence Unit (FIU) has implemented a customer monitoring program to meet regulatory obligations, support internal stakeholder investigations, and ensure that external constituents have robust compliance programs in place. The FIU is responsible for large-scale data analysis, alert dispositioning, and ad-hoc investigations using AML typologies, rules, and multiple internal data sources to monitor customer behavior and support compliance investigations. The MTS (Mastercard Transaction Services) organization supports the FIU by providing advanced analytical capabilities and scalable data processes. The Analyst, Legal Compliance role sits within MTS and reports to the Manager, Legal Compliance. This position is highly data-driven and supports the FIU by conducting AML-related activities through advanced data extraction, manipulation, and analysis as part of the transaction monitoring and investigation lifecycle. Working under general supervision, the analyst will leverage strong analytical and technical skills—particularly SQL and Excel—to analyze very large datasets, identify patterns, assess risk factors, and document findings through clear investigative narratives. ROLE • Conduct AML transaction monitoring, ad-hoc investigations, and research through deep data analytics across large datasets covering multiple regions and countries • Extract, query, and prepare data from internal databases (e.g., Oracle, data warehouse tables, system applications) to support investigations • Utilize SQL and advanced Excel (Power Pivot, pivot tables, formulas) to analyze datasets that may include tens of millions of records • Apply data mining techniques to identify behavioral patterns, anomalies, relationships, and meaningful insights within complex data sets • Summarize analytical findings, trends, and red flags in clear written investigative narratives and reports • Continuously develop technical and analytical expertise through training, self-study, and exposure to evolving AML typologies and data methodologies All About You Experience: • Bachelor’s degree required, experience in data analysis, financial operations, payments, risk management, or compliance-related fields • 2–3 years of experience in data analysis, transaction monitoring, or investigative analytics (AML experience is a plus but not mandatory if data expertise is strong) • Familiarity with AML, BSA, USA PATRIOT Act, and OFAC regulations preferred ACAMS or similar certification preferred Knowledge / Technical Skills (Key emphasis) • Advanced Microsoft Excel skills required, including Power Pivot, pivot tables, and complex formulas • Strong understanding of data extraction, cleaning, manipulation, and summarization methodologies • Hands-on experience with SQL (or similar languages), including modifying existing queries/scripts to extract data for specific investigations • Proven ability to analyze large, complex datasets, identify trends, and translate data into defensible conclusions • Experience working with compliance, risk, or investigative data is a plus Personal Attributes • Ability to quickly learn and apply payments industry terminology and AML-specific data context • Strong attention to detail with the ability to produce accurate, ... (truncated, view full listing at source)
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