PayPal is looking to combat money laundering by developing and implementing advanced data science models and algorithms to build monitoring solutions.
Requirements
- Minimum of three years of experience in the field of AML transaction monitoring, fraud detection, and AML/CFT
- Minimum of two years of experience working with development, tuning and optimization of AML transaction monitoring rules and reports, by leveraging data and statistical analysis techniques to derive thresholds, identify outliers and utilize statistical sampling techniques to facilitate above-the-line and below-the-line testing
- Thorough understanding of AML typologies, as well as transaction monitoring processes used to mitigate these risk typologies
- Good understanding of transaction monitoring systems – custom built or vendor systems such as Oracle Mantas, Actimize etc. - and the standard monitoring rules/scenarios offered
- Strong SQL skills using tools like Teradata, MS SQL, MySQL, Hadoop, Big Query
- Experience in building and developing models, queries, or software to analyze and visualize data using tools such as Tableau
- Ability to analyze large sets of complex data, draw meaningful conclusions, and make business recommendations based on analysis
Responsibilities
- Lead the development and implementation of advanced data science models.
- Implement monitoring solutions in a fast-paced environment while driving best practices in data science, ensuring data quality.
- Development of AML and Brand Risk Management (BRM) transaction monitoring rules to provide risk coverage, as well as tuning and optimization of transaction monitoring rules to improve efficiency and effectiveness of the rules
- Leveraging data and statistical analysis techniques to derive thresholds, identify outliers and utilize statistical sampling techniques to facilitate above-the-line and below-the-line testing
- Building and developing models, queries, or software to analyze and visualize data using tools such as Tableau
- Analyze large sets of complex data, draw meaningful conclusions, and make business recommendations based on analysis
- Structure and refine analysis with the goal of distilling insights from the data
Other
- Collaborate with stakeholders to understand requirements.
- Mentor and guide junior data scientists.
- Stay updated with the latest trends in data science.
- Strong research and analytical skills, business acumen, strategic and creative thinking, project leadership skills and multi-tasking capabilities
- Strong written and oral communication skills, with the ability to communicate to all levels of the business
