Job description

Description Data Analyst – Banking / Financial Crime We are seeking an experienced Data Analyst with strong banking and financial-crime experience to support data analysis, model tuning, optimization, and performance evaluation initiatives across sanctions, fraud, and AML. Key Responsibilities • Analyze and support Sanctions, Fraud, and AML models , including model tuning, optimization, and performance monitoring. • Apply appropriate model tuning methodologies and tools to improve model effectiveness and reduce false positives. • Analyze banking products, processes, systems, and transaction data to identify trends, patterns, and potential data or modeling issues. • Document model tuning methodologies, results, and optimization activities, and prepare reports and presentations for senior management and regulatory stakeholders . • Perform quantitative analysis to evaluate model performance and identify opportunities for improvement. • Develop and analyze features and datasets to support statistical modeling and machine learning initiatives. • Collaborate with data scientists, model risk teams, technology teams, compliance professionals, and business stakeholders. • Work with large datasets and develop automation to improve data analysis and model-tuning processes. • Clearly document and communicate analytical findings and recommendations to interdisciplinary teams. • Manage multiple priorities effectively in a fast-paced environment with changing business requirements. Required Qualifications • Experience in Sanctions, Fraud, AML, or financial-crime modeling . • Strong understanding of model tuning methodologies, optimization techniques, and related tools . • Strong knowledge of banking products, processes, systems, and financial transactions . • Advanced proficiency in Python and SQL , including experience working with large datasets and developing automated analytical solutions. • Strong Python programming skills for data analysis, feature engineering, statistical analysis, and modeling . • Experience developing and evaluating classification models, including: • Logistic Regression • Multinomial Logistic Regression • XGBoost • LightGBM • Random Forest • Ability to compare model performance using appropriate statistical and model-evaluation techniques. • Strong understanding of statistics, data science, and quantitative analysis . • Ability to identify, troubleshoot, and resolve data-quality and modeling issues. • Experience with version control systems such as Git/GitHub . • Master's or Ph.D. in Statistics, Economics, Finance, Mathematics, Data Science, or a related quantitative discipline . • Excellent written and verbal communication skills, with the ability to explain technical findings to both technical and non-technical stakeholders. • Strong organizational skills and the ability to manage multiple projects and shifting priorities effectively. Why Matrix Benefits: • Competitive base salary. • Comprehensive benefits package, including medical, dental, 401K, STD, HSA, PTO, and more. Join Us: Come and join a winning team! You'll be challenged, have fun, and be part of a highly respected organization. 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 .

Requirements

Must-haves

Data Analyst – Banking / Financial Crime
We are seeking an experienced Data Analyst with strong banking and financial-crime experience to support data analysis, model tuning, optimization, and performance evaluation initiatives across sanctions, fraud, and AML.
Analyze and support Sanctions, Fraud, and AML models , including model tuning, optimization, and performance monitoring.
Apply appropriate model tuning methodologies and tools to improve model effectiveness and reduce false positives.
Analyze banking products, processes, systems, and transaction data to identify trends, patterns, and potential data or modeling issues.
Document model tuning methodologies, results, and optimization activities, and prepare reports and presentations for senior management and regulatory stakeholders .
Perform quantitative analysis to evaluate model performance and identify opportunities for improvement.
Develop and analyze features and datasets to support statistical modeling and machine learning initiatives.
Collaborate with data scientists, model risk teams, technology teams, compliance professionals, and business stakeholders.
Work with large datasets and develop automation to improve data analysis and model-tuning processes.
Clearly document and communicate analytical findings and recommendations to interdisciplinary teams.
Manage multiple priorities effectively in a fast-paced environment with changing business requirements.
Experience in Sanctions, Fraud, AML, or financial-crime modeling .
Strong understanding of model tuning methodologies, optimization techniques, and related tools .
Strong knowledge of banking products, processes, systems, and financial transactions .
Advanced proficiency in Python and SQL , including experience working with large datasets and developing automated analytical solutions.
Strong Python programming skills for data analysis, feature engineering, statistical analysis, and modeling .
Experience developing and evaluating classification models, including:
Logistic Regression
Multinomial Logistic Regression
Random Forest
Ability to compare model performance using appropriate statistical and model-evaluation techniques.
Strong understanding of statistics, data science, and quantitative analysis .
Ability to identify, troubleshoot, and resolve data-quality and modeling issues.

Nice-to-haves

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Application prep

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Keywords to mirror

machine learningpythonsql

Platform: comeet
Effort: medium

Benefits

Benefits detected in the listing.

Dental

401k

Pto