Improving the efficiency and scalability of PayPal's sanctions screening and compliance systems, reducing false positives, addressing adjacent compliance risks, and enhancing customer experience.
Requirements
- Proficiency in SQL, BigQuery, Python, R, Tableau, and Power BI, with strong analytical and problem-solving skills.
- Experience with and advanced understanding of SQL queries, data structure and data profiling
- Working knowledge of Hadoop, Hive, Jupyter Notebooks; data warehouse skills is highly desirable
- Demonstrated ability to develop data-driven solutions for complex business challenges, fostering trust and collaboration across cross-functional teams.
- Advanced research, analytical, and project leadership skills, with a strong business acumen and multitasking ability.
- Skilled in presenting complex quantitative analyses to business stakeholders in a clear, accessible manner.
- Thorough understanding of economic sanctions programs administered by regulators such as OFAC, EU, UN, CSSF, etc., and associated adjacency risk.
Responsibilities
- Lead the development and implementation of advanced data science models.
- Drive best practices in data science.
- Ensure data quality and integrity in all processes.
- Own and lead the Screening Strategy & Enablement Adency program, driving aligned objectives to detect and mitigate sanctions-related risks effectively while reducing friction for legitimate customers.
- Interpret new regulatory requirements and collaborate with regional MLROs to finalize business requirements, and translate them into actionable data-driven solutions, then work with engineer team to implement these changes effectively.
- Lead the end-to-end development and implementation of sanctions screening solutions, ensuring scalability and alignment with business and regulatory goals.
- Lead initiatives to improve algorithmic filtering strategies, prioritizing the reduction of false positives while maintaining high levels of sensitivity and accuracy in sanctions screening processes.
Other
- Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
- Bachelor’s degree with a minimum of six years of experience in sanctions transaction Screening, profile screening, and AML, including at least three years in data analytics or data science.
- Excellent written and verbal communication skills, with the ability to effectively translate data insights into actionable business recommendations.
- Strong intellectual curiosity, strategic thinking, and a passion for solving problems, with comfort navigating ambiguity.
- Capable of managing multiple projects in a fast-paced, dynamic environment with independence and initiative.
