Job Summary

We are seeking a PEP Data Scientist to pivot and align global Politically Exposed Person (PEP) screening strategies with regional nuances. This role will design data-driven solutions that harmonize policies across jurisdictions, balancing local regulatory requirements with global compliance standards.

The successful candidate will translate complex datasets into actionable, scalable strategies that optimize PEP detection and minimize false positives. This position requires extensive cross-functional collaboration across engineering, advisory, and regulatory teams to ensure alignment with business objectives and global compliance expectations.

Key Responsibilities

• Drive comprehensive initiatives to strengthen PEP screening capabilities across all regions, ensuring detection and risk mitigation objectives align with regulatory expectations while maintaining seamless customer experiences.
• Collaborate with First Line of Defense, product management, engineering, and business units to develop strategic frameworks and roadmaps for global PEP screening initiatives.
• Oversee the complete development lifecycle of PEP screening solutions—from concept through implementation—ensuring scalability, performance, and compliance alignment.
• Analyze and interpret emerging regulatory requirements, working closely with regional MLROs to establish clear Business Requirement Documents (BRDs) and translate guidance into actionable, data-driven solutions.
• Partner with engineering teams to implement regulatory changes and system enhancements across production environments.
• Work with advisory and regional policy teams to refine PEP list definitions and classification criteria, ensuring comprehensive risk coverage.
• Conduct advanced data exploration and statistical analysis to identify inefficiencies in screening workflows, providing actionable recommendations for process improvements.
• Analyze large-scale datasets to extract meaningful insights, develop recommendations, and present findings that drive business decisions.
• Provide technical mentorship and business guidance to junior data scientists, fostering team capability and development.
• Collaborate with engineering teams to ensure real-time integration and deployment of analytical solutions, maintaining reliability and performance standards.

Requirements

Minimum Qualifications

• Minimum of 5 years of relevant professional experience and a Bachelor’s degree (or equivalent experience).

Preferred Qualifications

• Bachelor’s degree with a minimum of five years’ experience in sanctions transaction screening, PEP and negative news screening, or AML, including at least three years in data analytics or data science.
• In-depth understanding of PEP screening and sanctions programs administered by regulators such as OFAC, EU, UN, CSSF, and related adjacency risks.
• Proficiency in SQL (Google Cloud BigQuery), Python (Pandas, Numpy, PySpark), R, Tableau, and Power BI.
• Strong data manipulation, profiling, and analysis skills; familiarity with Lexis Nexis WorldCompliance+ data source.
• Experience with Hadoop, Hive, Jupyter Notebooks, and data warehouse environments highly desirable.
• Excellent written and verbal communication skills, capable of translating analytical insights into actionable business recommendations.
• Proven ability to design and implement data-driven compliance solutions for complex global operations.
• Strong intellectual curiosity, strategic thinking, and comfort navigating ambiguity.
• Advanced research, analytical, and project leadership skills with solid business acumen.
• Ability to manage multiple priorities in a fast-paced, global environment.
• Skilled in presenting complex quantitative analyses clearly to non-technical stakeholders.

Originally posted on