The Data Scientist role involves analyzing complex datasets, developing predictive models, and providing actionable insights to drive business decisions, specifically focusing on risk and fraud analytics. The role requires expertise in machine learning, statistical methods, and data-driven strategies to detect risky behaviors and prevent fraudulent activities.
Location: Washington, District of Columbia, Georgia, United States,
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.
Required Skills & Certifications:
- 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.
- 5+ years of proficiency in Python, SQL, SAS, and machine learning techniques.
- 5+ years of 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.
- 5+ years of experience with visualization tools like Tableau and Power BI.
- 5+ years of experience in responsible use of AI if used in solution design.
- Strong analytical skills and the ability to identify patterns and trends from data.
Preferred Skills & Certifications:
- 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.
Special Considerations:
Scheduling:
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