AML Banking Data Analyst & Model Tuning Expert

Matrix Global Services Limited; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

Matrix is seeking an experienced Data Analyst with a strong banking background and expertise in financial crime analytics, including sanctions, fraud, or AML modeling. You will develop, tune, and evaluate classification and ML models using Python and SQL, working with large banking datasets to improve detection systems.

The role focuses on model development, performance evaluation, and collaboration with cross-functional teams to address analytical challenges, with opportunities to present

Qualifications

• Master's or Ph.D. in Statistics, Economics, Finance, Mathematics, Data Science, or a related quantitative discipline.
• Experience in the banking or financial services industry, preferably in sanctions, fraud, or AML modeling.
• Strong understanding of model tuning methodologies, optimization techniques, and performance evaluation.
• Good knowledge of banking products, processes, systems, and financial crime risk.
• Hands-on experience developing and evaluating classification and machine learning models, including Logistic Regression, Multinomial Logit, XGBoost, LightGBM, Random Forest.
• Advanced proficiency in Python and SQL, including production-quality code for data analysis, feature engineering, and modeling.
• Experience with large datasets, automation, and data processing.
• Familiarity with Git/GitHub.

Responsibilities

• Perform quantitative analysis and model tuning across sanctions, fraud, and AML use cases.
• Develop, validate, and optimize statistical and ML models to improve detection accuracy and performance.
• Apply tuning methodologies and analytical tools to identify optimization opportunities.
• Develop and evaluate classification models (logistic regression, multinomial logit, tree-based methods).
• Use Python and SQL to perform data analysis, feature engineering, and statistical modeling.
• Work with large datasets to identify data quality issues, modeling gaps, and improvement opportunities.
• Document tuning methodologies, results, performance metrics, and optimization activities.
• Prepare reports and present findings to senior management, regulators, and cross-functional teams.
• Collaborate with business, technology, compliance, and governance teams on analytical challenges.
• Maintain code quality and version control using GitHub.

Skills

Quantitative analysis

Analytical skills

Model development

Data analysis

Education

Master's or PhD in a quantitative field

Tools

Python

SQL

Git/GitHub

Job description

Matrix is seeking an experienced Data Analyst with a strong banking background and expertise in financial crime analytics, including sanctions, fraud, or AML modeling. You will develop, tune, and evaluate classification and ML models using Python and SQL, working with large banking datasets to improve detection systems.

The role focuses on model development, performance evaluation, and collaboration with cross-functional teams to address analytical challenges, with opportunities to present