Senior Analyst - Financial Crime Control

We are looking for a Senior Analyst Financial Crime Control Unit to support the identification, assessment, and mitigation of financial crime risks across the organization's operations. The role involves conducting advanced analytics to detect suspicious activities, enhance anti-financial crime controls, and ensure regulatory compliance.

The ideal candidate will have strong analytical skills, experience working with large datasets, and expertise in financial crime detection, AML, or fraud analytics. You will work closely with cross-functional teams to develop detection strategies, identify emerging risks, and improve monitoring frameworks.

Key Responsibilities :

- Analyze large and complex datasets from multiple sources to identify suspicious transactions, financial crime patterns, and mule account activities.

- Perform in-depth analysis to detect trends, anomalies, and emerging financial crime risks.

- Conduct ad hoc investigations and prepare reports highlighting key findings and actionable insights.

- Develop and enhance detection models, monitoring scenarios, and rule sets to improve financial crime detection.

- Collaborate with Customer Due Diligence (CDD), Compliance, Risk, and Data teams to identify new typologies and strengthen monitoring controls.

- Utilize analytical tools such as SQL, Python, R, Excel, and Power BI to generate insights and support decision-making.

- Support financial crime risk assessments across products, customer segments, and geographies.

- Recommend control enhancements based on analytical findings and emerging threats.

- Ensure timely escalation of suspicious activities and maintain accurate MIS and reporting.

- Contribute to continuous improvement initiatives within the Financial Crime Control Unit.

Required Skills & Qualifications :

- Bachelor's degree in Finance, Statistics, Computer Science, Data Analytics, or a related field.

- Experience in Financial Crime, AML, Fraud Analytics, Risk Analytics, or Compliance Analytics.

- Strong analytical and logical problem-solving skills with the ability to interpret complex datasets.

- Hands-on experience with SQL, Python, R, Excel, and Power BI.

- Knowledge of financial crime typologies, mule account detection, transaction monitoring, and AML frameworks.

- Excellent report writing, communication, and stakeholder management skills.

- Ability to work collaboratively in a fast-paced, data-driven environment.