Fraud Data Scientist

Fraud Data Scientist

Responsibilities:

- Develop and deploy advanced machine learning models for fraud detection and prevention.

- Analyze large datasets to identify fraud patterns, anomalies, and trends.

- Conduct exploratory data analysis and feature engineering to enhance model performance.

- Implement real-time fraud detection systems and algorithms.

- Develop and maintain fraud risk assessment models and scoring systems.

- Collaborate with fraud investigators and business stakeholders to understand fraud scenarios and requirements.

- Communicate findings and insights to technical and non-technical audiences through reports and presentations.

- Stay up-to-date with the latest advancements in fraud detection technologies and techniques.

- Develop and implement fraud monitoring and alerting systems.

- Evaluate and improve the performance of existing fraud detection models.

- Develop and implement data quality checks and validation processes.

- Conduct research and experiments to identify new fraud detection opportunities.

- Design and implement A/B testing to evaluate the effectiveness of fraud prevention strategies.

Qualifications:

- Proficiency in programming languages such as Python or R.

- Experience with big data platforms and tools (e. , Hadoop, Spark).

- Strong understanding of fraud domain knowledge and risk management principles.

- Excellent analytical and problem-solving abilities.

- Excellent communication, presentation, and interpersonal skills.

- Ability to work independently and manage multiple projects