Description
Data Scientist/Modeler Role Description
The Data Scientist/Modeler will own the end-to-end AML modeling infrastructure, including data pipelines, model development, and deployment. The role requires deep expertise in data science, statistical modeling, and machine learning to support and enhance AML decision-making.
Job Description
Design, develop, and deploy machine learning models for AML applications, including fraud detection and risk assessment.
Own the entire AML modeling infrastructure, ensuring its robustness and scalability.
Develop data pipelines and preprocessing techniques for modeling workflows.
Conduct exploratory data analysis, feature engineering, and algorithm selection.
Evaluate model performance using statistical and business-driven metrics.
Collaborate with AML teams to align model outputs with compliance and operational requirements.
Provide technical documentation and training to stakeholders.
Stay updated on the latest advancements in machine learning and data science technologies.
Mandatory Skills
Strong expertise in data science and machine learning (5+ years).
Proficiency in Python, R, or other relevant programming languages.
Experience in building, deploying, and maintaining ML models in production.
Familiarity with AML use cases, such as anomaly detection and predictive analytics.
Solid understanding of data pipelines, ETL processes, and big data platforms.
Strong problem-solving and analytical skills.
Ability to work onsite with effective communication skills for cross-functional collaboration.