Fraud Data Scientist

SUMMARY:
A leading financial industry partner is looking for a highly analytical Fraud Data Scientist to join their team!

POSITION INFO:
Job Description
A leading financial institution is seeking a data scientist to join their fight against fraud. In this role, you will use your expertise to uncover hidden patterns in data and develop solutions that empower better decision-making. Your efforts will directly contribute to protecting customers and positioning the organization as a key player in national fraud prevention.
Here's a breakdown of what you'll be doing:

• Analyze vast datasets to identify emerging fraud trends and vulnerabilities.
• Develop and maintain fraud detection models that are both accurate and minimize disruptions to legitimate transactions.
• Continuously improve existing systems and processes to stay ahead of evolving fraud tactics.

• Align & Communicate Effectively: Ensure project deliverables directly support departmental strategy. Clearly document your work, ensuring everyone understands the goals and progress is regularly reviewed.
• Fraud & Analytics Expertise: Provide deep knowledge and guidance for future data-driven projects focused on fraud and analytics.
• Optimizing Detection Models: Continuously review, analyze, and improve core models used to detect fraud in the organization's payment systems.
• Client Risk Management: Balance client needs for accurate fraud detection with minimizing disruptions to legitimate transactions. This involves adjusting models and thresholds based on factors like desired alert volume and acceptable false positive rates.
• Troubleshooting & Performance Monitoring: Investigate unusual system outputs and troubleshoot any issues that may arise. Regularly monitor system performance using various metrics, both industry-wide and for individual clients.
• Data Management & Quality: Manage data quality issues related to fraud detection. Integrate new data sources when needed to improve model effectiveness. Assist data engineering efforts to ensure the acquisition of high-quality fraud data. Evaluate data cleaning processes to minimize errors before analysis.
• Bridge the Gap: Clearly communicate technical concepts to non-technical audiences.
• Actionable Insights: Contribute to departmental publications that translate data analysis into clear and actionable insights, following established best practices in data science.

• Bachelor in Science degree (Applied Mathematics, Financial Mathematics, Statistics or Actuarial)
• Masters degree preferred

• Minimum 4 years of experience in a relevant field, such as financial data analysis.
• Strong analytical skills with experience in big data processing and manipulation.
• Proficiency in scripting and programming languages commonly used for data analysis.
• Experience applying statistical modelling techniques to solve complex problems.
• Familiarity with the financial industry and its data structures is a plus.
• Prior experience developing or working with fraud detection models is highly desirable.
• Experience in data wrangling to prepare data for analysis is essential.
• Strong competency in Microsoft Office Suite and SQL is required.
• Experience with machine learning techniques, Oracle database systems, NetReveal fraud detection platform, RStudio, and Python is a significant advantage.

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