Banking Data Analyst: Fraud & AML Specialist

Matrix USA; United States; On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits

Job summary

Matrix is seeking a Data Analyst with strong banking and financial-crime experience to support data analysis, model tuning, optimization, and performance evaluation across sanctions, fraud, and AML.

The role involves collaborating with data scientists, model risk, technology, compliance, and business stakeholders to develop features and datasets for ML initiatives and to automate analysis on large datasets.

Qualifications

• Experience in sanctions, fraud, AML, or financial-crime modeling.
• Advanced proficiency in Python and SQL with large datasets and automated solutions.
• Experience developing and evaluating classification models: Logistic Regression, XGBoost, LightGBM, Random Forest.
• Excellent written and verbal communication to stakeholders.

Responsibilities

• Analyze and support Sanctions, Fraud, and AML models, including tuning and performance monitoring.
• Apply model tuning methodologies and tools to improve effectiveness and reduce false positives.
• Analyze transactions and systems to identify trends and data issues.
• Document tuning methodologies, results, and prepare reports for senior management and regulators.
• Perform quantitative analysis to evaluate model performance and improvement opportunities.
• Develop features and datasets to support statistical modeling and ML initiatives.
• Collaborate with data scientists, model risk, technology, compliance, and business stakeholders.
• Work with large datasets and automate data analysis and model-tuning processes.
• Communicate findings and recommendations clearly to interdisciplinary teams.
• Manage multiple priorities in a fast-paced environment with changing requirements.

Skills

Python

SQL

Model tuning

Data analysis

Statistics

XGBoost

LightGBM

Random Forest

Machine learning

Communication

Education

Master's or Ph.D. in Statistics, Economics, Finance, Mathematics, Data Science, or related quantitative discipline

Tools

Git/GitHub

Job description

Matrix is seeking a Data Analyst with strong banking and financial-crime experience to support data analysis, model tuning, optimization, and performance evaluation across sanctions, fraud, and AML.

The role involves collaborating with data scientists, model risk, technology, compliance, and business stakeholders to develop features and datasets for ML initiatives and to automate analysis on large datasets.