Data Scientist

1 week ago

Atlanta, GA, United States h3 Technologies Full time

Position Title Data Scientist
Job Location Atlanta, GA, USA
Hybrid
Must have Skills/Attributes AI Models, Data Scientist, Design, Python, SAS, SQL

Position Description
Required Education:
• Bachelor's degree in data science, Computer Science, Statistics, Mathematics, Economics or a related field
Preferred Education:
• Master's degree in data science, Computer Science, Statistics, Mathematics, Economics or a related field
Required Experience, Knowledge, and Skills:
• Familiarity with graph analytics or network-based fraud detection tools
• Knowledge of regulatory frameworks and compliance issues related to fraud and financial crime
• Strong communication skills with the ability to explain technical solutions to non-technical stakeholders
• Professional experience in data science (10 Years)
• Proficient in Python, SQL, SAS, and machine learning techniques (5 Years)
• Experience working with large datasets and cloud platforms (e.g., AWS, GCP, Azure) (5 Years)
• 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 (5 Years)
• Experience in responsible use of AI if used in solution design (5 Years)
• Strong analytical skills and the ability to identify patterns and trends from data
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
• Translate business problems into data-driven solutions with measurable impact
• Develop and 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 and monitor KPIs to evaluate model performance and improve fraud detection systems over time
• Conduct deep-dive investigations into fraud cases, creating detailed reports and actionable insights
• Stay current with emerging fraud techniques, industry best practices, and data science tools

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