Offer summary

Qualifications:

Bachelor's degree in data analytics or related field., Minimum of 7 years of experience in data analysis, especially in financial crimes or AML., Proficiency in SQL, Python, R, and SAS for data analysis., Strong understanding of AML/KYC regulations and experience in modeling and root cause analysis..

Key responsibilities:

Analyze transactions, accounts, and customer data to identify suspicious patterns.

Use analytical and visualization tools to support investigations and decision-making.

Perform data cleaning, validation, and ETL processes.

Design and implement financial crime detection models and scenarios.

Job description

We are seeking a highly skilled and experienced Senior Data Analyst to join our Financial Crimes / Anti-Money Laundering (AML) team. The ideal candidate will have a strong technical background and extensive experience in financial crimes and AML space. This role involves analyzing and interpreting transactions, accounts, customers, alerts, and third-party data using advanced statistical and analytical tools to identify potential suspicious patterns, anomalies, and risks.

Responsibilities:

Analyze and interpret transactions, accounts, customers, alerts, and third-party data using statistical and analytical tools to identify potential suspicious patterns, anomalies, and potential risks.
Utilize data analytics tools (e.g., SQL, Python, R, SAS) and data visualization tools (e.g., Tableau, PowerPoint) to support investigations teams and decision-making processes.
Perform data ETL, cleaning, and validation.
Design and implement financial crime detection models and scenarios.
Conduct root cause analyses on financial crime incidents to enhance detection and prevention strategies.
Translate data-driven forensic analyses into actionable insights for investigators, enabling effective and efficient investigations.

Qualifications:

At least a bachelor's degree in data analytics or a related field.
At least 7 years of experience in the field.
Proven experience in financial crimes/AML space.
Proficiency in data analytics tools such as SQL, Python, R, and SAS.
Experience with data visualization tools like Tableau and PowerPoint.
Strong understanding of AML/KYC regulations and practices.
Experience in designing and implementing financial crime detection models and scenarios.
Ability to conduct root cause analyses on financial crime incidents.
Excellent analytical and problem-solving skills.
Strong communication skills, with the ability to translate complex data into actionable insights.

Experience working in a major financial institution or consulting firm preferred.
Advanced degree in a related field (e.g., Data Science, Statistics, Finance) preferred.

This is a contract position.

This role is work from home (Brazil).

Required profile