Senior AML Data Analyst – Banking & ML Modeling

Matrix IT Ltd; United States; Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Matrix IT Ltd seeks an experienced Data Analyst with a banking background to advance financial crime analytics, including AML modeling and sanctions. You will design and tune classification models, validate performance, and drive improvements across large banking datasets using Python and SQL.

The role focuses on delivering production-ready analytics, collaborating with compliance, IT, and business teams, and presenting insights to senior leaders. Prior AML modeling experience is required.

Formación

• Master's or PhD in Statistics, Economics, Finance, Mathematics, Data Science, or related quantitative discipline.
• Experience in banking or financial services, 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, and 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.
• Strong understanding of statistical concepts, data science methodologies, and model performance evaluation.
• Familiarity with version control tools such as Git and GitHub.

Responsabilidades

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

Conocimientos

Python

SQL

Data analysis

Machine learning

Model tuning

Statistics

Git/GitHub

Educación

Master's or PhD in a quantitative field

Herramientas

XGBoost

LightGBM

Random Forest

Logistic Regression

Multinomial Logit

Descripción del empleo

Matrix IT Ltd seeks an experienced Data Analyst with a banking background to advance financial crime analytics, including AML modeling and sanctions. You will design and tune classification models, validate performance, and drive improvements across large banking datasets using Python and SQL.

The role focuses on delivering production-ready analytics, collaborating with compliance, IT, and business teams, and presenting insights to senior leaders. Prior AML modeling experience is required.