AML Business Data Analyst

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

Job summary

Matrix seeks an experienced Data Analyst with a strong banking background and expertise in financial crime analytics. You will develop and tune classification models (logistic regression, multinomial logit, XGBoost, LightGBM, RF) and perform data analysis using Python and SQL.

The role focuses on sanctions, fraud, and AML use cases, evaluating model performance, and presenting findings to senior management and regulators. Collaboration across functions is essential.

Qualifications

• Master's or PhD in Statistics, Economics, Finance, Mathematics, Data Science or related quantitative field.
• Experience in banking or financial services, sanctions, fraud, or AML modeling preferred.
• Proficient in Python and SQL with production-quality coding ability.

Responsibilities

• Perform quantitative analysis and model tuning for sanctions, fraud, and AML use cases.
• Develop, validate, and optimize statistical and ML models for detection accuracy.
• Apply tuning methodologies to identify opportunities for model optimization.
• Develop and evaluate classification models including logistic regression, multinomial logit, and tree-based models (XGBoost, LightGBM, RF).
• Use Python and SQL for data analysis, feature engineering, modeling, and automation.
• Work with large datasets to identify data quality issues and modeling gaps.
• Compare model performance using statistical measures and recommend optimizations.
• Document tuning methodologies, results, and metrics.
• Prepare reports and present findings to senior management and regulators.
• Collaborate across business, technology, compliance, and governance teams.
• Maintain code quality and version control (GitHub).

Skills

Python

SQL

Statistical modeling

Machine learning

Data analysis

Model development

Education

Master's or PhD in Statistics or related

Tools

GitHub

Job description

Job Description: Data Analyst – Banking / Financial Crime Modeling

Position Overview

We are seeking an experienced Data Analyst with a strong banking background and expertise in financial crime analytics, including sanctions, fraud, or Anti-Money Laundering (AML) modeling. The ideal candidate will have strong quantitative and analytical capabilities, hands-on experience with model development and tuning, and advanced proficiency in Python and SQL.

This role will focus on analyzing complex banking data, developing and optimizing classification models, evaluating model performance, and supporting tuning initiatives to improve the effectiveness of financial crime detection systems.

Key Responsibilities

• 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 appropriate tuning methodologies and analytical tools to identify opportunities for model optimization.
• Develop and evaluate classification models, including logistic regression, multinomial logit, and tree-based machine learning algorithms such as XGBoost, LightGBM, and Random Forest.
• Use Python and SQL to perform data analysis, feature engineering, statistical modeling, and automation.
• Work with large and complex datasets to identify data quality issues, modeling gaps, and opportunities for improvement.
• Compare model performance using appropriate statistical measures and recommend optimization strategies.
• Document model tuning methodologies, results, performance metrics, and optimization activities.
• Prepare clear reports and present findings to senior management, regulatory stakeholders, and interdisciplinary teams.
• Collaborate with business, technology, compliance, and model governance teams to address analytical and modeling challenges.
• Maintain code quality and version control using tools such as GitHub.

Required Qualifications & Experience

• 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 and Multinomial Logit
• XGBoost
• LightGBM
• Random Forest
• Advanced proficiency in Python and SQL, including the ability to write production-quality Python code for data analysis, feature engineering, and statistical modeling.
• Experience working 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.

Core Competencies

• Strong quantitative, analytical, and problem-solving skills.
• Ability to identify, investigate, and resolve data quality and modeling issues.
• Excellent documentation and reporting capabilities, including the ability to communicate model tuning outcomes to senior management and regulators.
• Strong verbal and written communication skills.
• Ability to collaborate effectively with cross-functional and interdisciplinary teams.
• Adaptability and the ability to manage multiple priorities in a changing environment.

WHY JOIN US

Matrix is a global, dynamic, and fast‑growing technology services and consulting company with over 17,000 employees worldwide. Founded in 2001, Matrix has grown through significant organic expansion and strategic acquisitions, executing some of the largest and most impactful technology projects in the market.

We specialize in the design, development, and implementation of advanced technologies, software solutions, and digital products. Our services include infrastructure and consulting, IT outsourcing and offshore delivery, training and assimilation programs, and acting as a trusted implementation and delivery partner for the world’s leading software vendors.

With deep expertise across both the private and public sectors—spanning Finance, Telecom, Healthcare, Hi‑Tech, Education, Defense, and Security—Matrix serves a strong customer base in Israel alongside a continuously expanding global client portfolio.

At Matrix, our people are at the heart of our success. We are a community of talented, creative, and dedicated professionals who are passionate about innovation and excellence. We actively attract, develop, and retain top talent, recognizing that every employee’s contribution is critical to our continued growth and future success.

Matrix’s success is built on a challenging and engaging work environment, competitive compensation and benefits, and meaningful career development opportunities. We foster a diverse, inclusive culture that encourages collaboration, continuous learning, and growth—together.

Join the winning team. Be challenged, grow your career, and enjoy the journey in a highly respected global organization.

To learn more, visit: www.matrix-ifs.com

EQUAL OPPORTUNITY EMPLOYER: Matrix is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind. Matrix is committed to the principle of equal employment opportunity for all employees, providing employees with a work environment free of discrimination and harassment. All employment decisions at Matrix are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, family or parental status, or any other status protected by the laws or regulations in our locations. Matrix will not tolerate discrimination or harassment based on any of these characteristics. Matrix encourages applicants of all ages.