Business Data Analyst

Job not on LinkedIn

🔥 18 hours ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📉 Data Analyst

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.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

WebsiteLinkedInAll Job Openings

51 - 200 employees

📦 Logistics

💼 Consulting

🍽️ Food & Beverage

Logistics • Consulting • Food & Beverage

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

• Analyze and support Sanctions, Fraud, and AML models, including model tuning, optimization, and performance monitoring • Apply 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 • 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 • Document and communicate analytical findings and recommendations to interdisciplinary teams • Manage multiple priorities in a fast-paced environment with changing business requirements

🎯 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, XGBoost, LightGBM, and 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

🏖️ Benefits

• Competitive base salary • Comprehensive benefits package, including medical, dental, 401K, STD, HSA, PTO, and more • Meaningful career development opportunities • Challenging and engaging work environment • Diverse, inclusive culture that encourages collaboration, continuous learning, and growth