Expedite Technology Solutions LLC
GA DHS - Data Scientist
Expedite Technology Solutions LLC, Atlanta, Georgia, United States, 30383
Short Description:
In this role, you will analyze large and/or complex datasets, develop predictive models, and derive actionable insights that drive key business decisions.
Complete Description: We are seeking a highly analytical and detail-oriented Data Scientist with experience in Risk and Fraud analytics to join our growing team. This role will focus on developing and deploying machine learning models, statistical methods, and data-driven strategies to detect risky behaviors and prevent fraudulent activities across our products and services.
Key Responsibilities • Collect, clean, and analyze large, complex datasets from multiple sources. • Develop predictive models and machine learning algorithms to support decision-making and improve business performance. • Translatebusiness problems into data-driven solutions with measurable impact. - Develop nd deploy machine learning models to detect, predict, and prevent fraudulent transactions and behavior patterns. - Analyze large volumes of structured and unstructured data from multiple sources to identify fraud trends and root causes. - Collaborate with fraud operations, engineering, and compliance teams to implement real-time fraud detection solutions. - Design nd monitor KPIs to evaluate model performance and improve fraud detection systems over time. - Conduct deep-dive investigations into fraud cases, creating detailed reports and ctionable insights. - Stay current with emerging fraud techniques, industry best practices, and dat science tools. Required Qualifications - Bachelor's or master's degree in data science, Computer Science, Statistics, Mathematics, Economics or a related field. - 10+ years of professional experience in data science - Proficient in Python, SQL, SAS and machine learning techniques - Experience in responsible use of AI if used in solution design • Strong analytical skills and the ability to identify patterns and trends from data - Experience working with large datasets and cloud platforms (e.g., AWS, GCP, Azure). - Strong understanding of supervised and unsupervised fraud detection techniques, including anomaly detection, behavioral modeling, and network analysis. - Experience with visualization tools like Tableau and Power BI.
Complete Description: We are seeking a highly analytical and detail-oriented Data Scientist with experience in Risk and Fraud analytics to join our growing team. This role will focus on developing and deploying machine learning models, statistical methods, and data-driven strategies to detect risky behaviors and prevent fraudulent activities across our products and services.
Key Responsibilities • Collect, clean, and analyze large, complex datasets from multiple sources. • Develop predictive models and machine learning algorithms to support decision-making and improve business performance. • Translatebusiness problems into data-driven solutions with measurable impact. - Develop nd deploy machine learning models to detect, predict, and prevent fraudulent transactions and behavior patterns. - Analyze large volumes of structured and unstructured data from multiple sources to identify fraud trends and root causes. - Collaborate with fraud operations, engineering, and compliance teams to implement real-time fraud detection solutions. - Design nd monitor KPIs to evaluate model performance and improve fraud detection systems over time. - Conduct deep-dive investigations into fraud cases, creating detailed reports and ctionable insights. - Stay current with emerging fraud techniques, industry best practices, and dat science tools. Required Qualifications - Bachelor's or master's degree in data science, Computer Science, Statistics, Mathematics, Economics or a related field. - 10+ years of professional experience in data science - Proficient in Python, SQL, SAS and machine learning techniques - Experience in responsible use of AI if used in solution design • Strong analytical skills and the ability to identify patterns and trends from data - Experience working with large datasets and cloud platforms (e.g., AWS, GCP, Azure). - Strong understanding of supervised and unsupervised fraud detection techniques, including anomaly detection, behavioral modeling, and network analysis. - Experience with visualization tools like Tableau and Power BI.