AML​/Sanctions Data Scientist – Associate

• Utilize analytical techniques to address financial crime issues
• Engage with clients to foster meaningful professional relationships
• Apply SQL and Python for data analysis and problem-solving
• Explore machine learning, NLP, and LLMs in relevant projects
• Contribute to team efforts while enhancing personal technical skills
• Adapt to complex situations and develop strategic insights
• Participate in research to support project objectives
• Uphold professional standards and ethical guidelines

• Bachelor's Degree in Computer and Information Science, Computer and Information Science & Accounting, Economics, Economics and Finance, Economics and Finance & Technology, Engineering, Operations Management/Research, Statistics, Mathematics, Data Processing/Analytics/Science or related field
• 1 year of experience in data science/machine learning
• Interest in financial crime, AML, and fraud analytics
• Skilled in SQL for complex data queries
• Advanced Python skills for data manipulation
• Experience building and deploying machine learning models
• Understanding of machine learning concepts and algorithms
• Comfort working with structured and unstructured data
• Familiarity with agentic AI frameworks
• Hands-on experience with CI/CD pipelines for data science
• Proficiency in SQL and Python
• Basic understanding of machine learning algorithms and evaluation metrics
• Exposure to scikit-learn, XGBoost, and Hugging Face Transformers
• Other quantitative fields of study may be considered
• Ability to travel up to 60%

Demonstrates expertise in SQL and Python for data analysis, with a strong foundation in machine learning concepts and algorithms. Engages effectively with clients while upholding professional standards in financial crime and fraud analytics.

• SQL Data Querying
• Advanced Python Skills
• Machine Learning Model Deployment
• Financial Crime Analytics
• CI/CD Pipelines for Data Science

• Data Analysis
• Machine Learning
• NLP
• Data Manipulation
• Statistical Analysis
• Complex Data Queries
• Evaluation Metrics
• Agentic AI Frameworks
• Structured and Unstructured Data Handling
• Building Machine Learning Models

• Client Engagement
• Analytical Thinking
• Adaptability
• Team Collaboration
• Strategic Insight Development

• Financial Crime
• AML
• Fraud Analytics
• Data Science
• Machine Learning Concepts

• Scikit-learn
• XGBoost
• Hugging Face Transformers
• CI/CD Tools
• Data Processing Tools