AML Business Data Analyst

Job not on LinkedIn

🔥 1 hour ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📉 Data Analyst

👻 Ghost score 25%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Matrix Global

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Matrix Global is a company that revolutionizes the way the oil and gas industry transacts by providing a sophisticated auction platform for storage and pipeline capacities. Their proprietary MAP platform enhances transparency and competition within the midstream sector, allowing businesses to optimize storage transactions and manage risks effectively through both short-term and long-term contracts. By collaborating with industry leaders, Matrix Global offers strategic opportunities for storage providers and energy companies, fostering a dynamic marketplace for oil and gas transactions.

📋 Description

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

🎯 Requirements

• 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, and Random Forest • Advanced proficiency in Python and SQL, including 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 • Strong quantitative, analytical, and problem-solving skills • Ability to identify, investigate, and resolve data quality and modeling issues • Excellent documentation and reporting capabilities, including communicating 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 ability to manage multiple priorities in a changing environment

🏖️ Benefits

• Competitive compensation and benefits • Meaningful career development opportunities • Challenging and engaging work environment • Diverse, inclusive culture • Collaboration, continuous learning, and growth

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