Data Scientist – Enterprise Fraud

• Developing effective anomaly detection metrics and monitoring tools to identify potential fraud.
• Analyzing data to detect suspicious activity, identify fraud patterns, and surface emerging trends.
• Partnering closely with cross-functional teams to share insights and continuously improve fraud mitigation processes.
• Performs analytical tasks on vast amounts of structured and unstructured data to extract actionable business insights.
• Participates in the data gathering, data processing and data mining of large and complex datasets.
• Develops algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.
• Runs analytical experiments in a methodical manner to find opportunities for product and process optimization.
• Assists in the presentation of business insights to management using visualization technologies and data storytelling.

• 3+ years of relevant / direct industry experience
• Master’s education
• Analytical Thinking
• Competitive Advantages
• Data Analytics
• Data Mining
• Data Science
• Machine Learning (ML)

Demonstrates expertise in Data Analytics, Data Mining, and Machine Learning to develop effective anomaly detection metrics and monitoring tools. Capable of analyzing large datasets to extract actionable insights and optimize fraud mitigation processes through collaboration and data storytelling.

• Data Analytics
• Data Mining
• Machine Learning
• Analytical Thinking
• Data Science

• Anomaly Detection Metrics
• Fraud Detection
• Statistical Techniques
• Algorithm Development
• Data Processing
• Data Visualization
• Data Analysis
• Predictive Modeling
• Business Insights Extraction
• Data Experimentation

• Analytical Thinking
• Collaboration
• Communication

• Master’s Education

• Fraud Mitigation
• Cross-Functional Teams
• Structured Data
• Unstructured Data
• Emerging Trends