Job Summary:
We are seeking a highly skilled AML/Fraud Data Scientist with strong expertise in technology particularly in R or Python. The ideal candidate will have 4 to 7 years of experience in data science or analytical roles, and with domain knowledge demonstrating proficiency in detecting and preventing fraudulent activities.
Key Responsibilities:
- Develop and implement models and strategies to identify fraudulent/AML activities and mitigate risks using advanced analytical techniques.
- Utilize R, Python, and other analytical tools to analyze large datasets, identifying patterns and trends related to fraud and AML.
- Model Development: Create, test, and refine predictive models to forecast potential suspicious activities.
- Implement or review systems that monitors and analyze financial transactions, identifying suspicious activities and ensuring compliance with AML regulations.
- Conduct thorough risk assessments and develop risk profiles for clients and transactions to determine potential vulnerabilities.
- Prepare and submit regulatory reports related to AML and fraud, ensuring accuracy and compliance with relevant laws and regulations.
Key Requirements:
- 4 to 7 years of experience in data science, analytics, or a related role with a focus on AML and fraud detection.
- Proficiency in R and Python.
- Experience with data analysis tools and techniques.
- Familiarity with machine learning algorithms and statistical models.
- Strong analytical and problem-solving skills with the ability to interpret complex data and make data-driven decisions.
- Domain and practical knowledge on Fraud / AML.
- Relevant certifications in AML, Fraud Detection, or Data Science.
- Knowledge of big data technologies and platforms.
- Familiarity with the financial services industry and its regulatory environment.
