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Fraud Data Analyst - LexisNexis Risk Solutions
Data Analyst
Analyze large datasets to detect and prevent fraud, leveraging Python, SQL, machine learning, and data visualization to build predictive models and actionable insights for risk mitigation.
About the role
Key Responsibilities
- Collect, clean, and analyze large volumes of transactional and behavioral data to identify fraud patterns and emerging threats.
- Develop and maintain predictive models using machine learning techniques to score and flag suspicious activities.
- Collaborate with cross‑functional teams to integrate fraud detection insights into decision‑making tools and dashboards.
- Generate detailed reports and visualizations that communicate findings to stakeholders and support risk‑management strategies.
- Continuously monitor model performance, refine algorithms, and stay current with industry fraud trends and regulatory requirements.
Requirements
- Proven experience in data analysis and fraud detection within financial services or related sectors.
- Strong proficiency in Python, SQL, and data manipulation libraries (pandas, NumPy).
- Hands‑on experience with machine learning frameworks (scikit‑learn, TensorFlow, or similar) and model deployment.
- Excellent data visualization skills using tools such as Tableau, Power BI, or matplotlib.
- Analytical mindset with the ability to translate complex data into actionable business insights.
Skills
pythonsqlmachine learning