Senior Data Scientist

Description:

We seek a skilled and proactive AML Data Scientist to design, implement, and evaluate AI/ML-driven fraud detection models to identify and mitigate anti-money laundering (AML) activities and financial crimes. This role involves leveraging advanced machine learning, predictive analytics, and artificial intelligence techniques to analyze high-dimensional data, uncover potential risks, and enhance fraud detection capabilities.

Key Responsibilities:

Design, develop, and evaluate machine learning models to detect fraud, identify potential AML risks, and mitigate financial crimes.

Leverage predictive analytics, AI, and advanced statistical techniques to analyze high-dimensional and complex datasets.

Collaborate with clients and internal stakeholders to review, validate, and refine AML models, ensuring optimal functionality and effectiveness.

Build, manage, and execute the entire AI/ML program, taking full ownership of its implementation and continuous improvement.

Conduct thorough validation and stress testing of AML models to ensure accuracy and compliance with regulatory requirements.

Communicate progress, insights, and updates on the AI/ML program to management and other stakeholders.

Partner with cross-functional teams to integrate AI/ML solutions into operational workflows and existing AML systems.

Stay updated on industry trends, emerging threats, and advancements in AI/ML technologies to enhance fraud detection strategies.

Required Skills and Qualifications:

Proven experience as a Data Scientist, particularly in AML, fraud detection, or financial crime prevention.

Strong expertise in Python and advanced machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

Solid understanding of predictive analytics, AI, and data science techniques, with hands-on experience in handling high-dimensional data.

In-depth knowledge of AML models, financial crime regulations, and fraud detection methodologies.

Ability to take initiative and drive end-to-end implementation of AI/ML programs independently.

Strong problem-solving skills and the ability to translate business requirements into effective AI/ML solutions.

Excellent communication and presentation skills to convey complex technical concepts to stakeholders and management.

Preferred Qualifications:

Advanced degree in Data Science, Machine Learning, Statistics, or a related field.

Knowledge of regulatory compliance requirements in AML and financial crimes.

Experience with AML compliance platforms or tools, such as NICE Actimize or SAS AML.

Familiarity with cloud platforms (AWS, Azure, GCP) for deploying and scaling machine learning models.

Knowledge of big data technologies such as Spark or Hadoop is a plus.

Join a dynamic and innovative team where you can shape the future of fraud detection and AML solutions using cutting-edge AI/ML technologies. Your contributions will play a critical role in safeguarding financial systems and combating financial crimes.