Anti-Money Laundering Analyst

Financial Crime Analyst

Location: Hybrid – Mandaluyong

Work Arrangement: 3 days onsite | 2 days Work From Home

Schedule: Day Shift

• 9:00 AM – 6:00 PM, or
• 10:00 AM – 7:00 PM

Earn up to 65k-68k monthly (depending on your skills)

What You’ll Do

Join a compliance-focused Financial Crime team responsible for strengthening transaction monitoring and financial crime detection capabilities. You’ll combine analytical expertise, financial crime knowledge, and data-driven problem solving to identify emerging risks, improve detection effectiveness, and help create a better customer experience.

In this role, you will:

• Optimize AI-driven transaction monitoring systems by evaluating existing detection rules, models, and inputs across both vendor and in-house platforms.
• Analyze high-risk transactions and customer activity to identify unusual behavior, emerging typologies, patterns, and anomalies associated with money laundering, fraud, terrorist financing, and other financial crime risks.
• Evaluate and improve transaction monitoring effectiveness, using data and customer behavior insights to identify opportunities to enhance detection while reducing unnecessary false positives.
• Partner with Identity, Trust, Fraud, and Data teams to test and fine-tune machine learning models and improve financial crime detection accuracy.
• Develop and monitor financial crime risk metrics, dashboards, and reporting to measure system performance, identify trends, and understand the impact of controls on customers.
• Translate complex business problems into analytical solutions by developing hypotheses, building analytical frameworks, conducting in-depth analyses, and presenting clear, actionable recommendations.
• Design and evaluate experiments, interpret A/B testing results, and conduct ad hoc analysis to support data-driven decision-making.
• Stay current with AML/CFT and sanctions requirements, regulatory developments, emerging risks, and financial crime typologies to ensure detection strategies remain effective and compliant.
• Collaborate cross-functionally with Compliance, Legal, Operations, Risk, Data, and Identity & Trust teams to develop and implement effective financial crime prevention strategies.

What You’ll Bring

• 4+ years of experience in AML/CFT transaction monitoring analytics, fraud or risk analytics, financial crime, or a similar data-focused role.
• Strong SQL skills and proficiency in Python, R, or another programming language used for data analysis.
• Practical experience with AML/CFT transaction monitoring, detection strategies, risk scoring, and financial crime risk metrics.
• Experience using data visualization and business intelligence tools, such as Tableau or similar platforms.
• Strong understanding of AML/CFT and fraud regulations, financial crime typologies, and risks within the fintech or financial services industry.
• Experience working with machine learning, anomaly detection, or advanced analytical techniques is a plus.
• Experience with blockchain or cryptocurrency transaction analysis is a plus.
• Strong analytical and problem-solving skills, with the ability to identify meaningful insights from complex and sometimes ambiguous datasets.
• Excellent communication skills, with the ability to translate complex analytical findings into clear recommendations for both technical and non-technical stakeholders.
• A Bachelor’s degree or advanced degree in a quantitative discipline, such as Statistics, Mathematics, Economics, Computer Science, Data Science, or a related field.
• Experience working in a highly regulated or compliance-driven environment, with an understanding of how to balance effective risk controls with a positive customer experience.

I’d recommend using “Financial Crime Compliance Analyst (AML)” as the job title if you want the strongest combination of market familiarity and candidate searchability.