Data Scientist

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.