Candidates with technical expertise in AML analytics and machine learning, and experience in financial compliance, will find this role in Data, Systems and Innovation at Goldman Sachs in Richardson, TX, suits their background and skills.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Goldman Sachs
Global Compliance Our division prevents, detects and mitigates compliance, regulatory and reputational risk across the firm and helps to strengthen the firm’s culture of compliance. Compliance accomplishes these through the firm’s enterprise-wide compliance risk management program. As an independent control function and part of the firm’s second line of defense, Compliance assesses the firm’s compliance, regulatory and reputational risk; monitors for compliance with new or amended laws, rules and regulations; designs and implements controls, policies, procedures and training; conducts independent testing; investigates, surveils and monitors for compliance risks and breaches; and leads the firm’s responses to regulatory examinations, audits and inquiries. You'll be part of a team with members from a wide range of academic and professional backgrounds, such as law, accounting, sales, and trading. We look for those who possess sound judgment, curiosity, and are able to adapt to a changing regulatory landscape. Business Unit and Role Overview
Financial Crime Compliance (“FCC”) has primary responsibility for the execution of the firm’s enterprise-wide Anti-Money Laundering (“AML”), anti-bribery, and government sanctions compliance programs and, among other things, performs enhanced due diligence and government sanctions screening, as well as surveillance and investigations designed to identify potential terrorist financing, money laundering, bribery, market abuse, or other suspicious activity.
Opportunity
FCC is seeking an individual to join its FCC Data, Systems and Innovation team to assist in implementing and operating transaction monitoring surveillance models, model tuning and building AML Analytics across the firm’s businesses. S/he will be working with cross-divisional partners, including technology, operations and business personnel through all aspects of strategic and tactical builds of a critical transaction monitoring program, including but not limited to the following:
Capturing, analyzing and documenting business requirements and functional specificationsData sourcing, data analysis and identifying data requirementsAssist in development and implementation of AML AnalyticsAssist in integration of Machine Learning and Artificial Intelligence ML/AI into AML ModelsData and surveillance validation planning and executionConduct investigative and Testing reviews of FCC’s controls and related partnered controlsDraft detailed investigative and Testing reports, including opinions, findings and corrective action plansUtilize and apply statistical measures, machine learning algorithms to track and improve efficiency of Anti-Money Laundering (AML) surveillancesDocumentation of project artifacts for Compliance testing, Model Validation, regulatory and audit purposes
The successful candidate will have strong analytical skills, the ability to collaborate with others, manage workflows and multi-task. The team member is expected to quickly gain an understanding of the firm’s global transaction banking businesses, and the rules and regulations under which the Bank operates.
The role is open to start immediately.
Basic Qualifications:
3-5 years of prior experience in an analytical role in Financial Crimes Compliance, preferably in Global Transaction Banking, Corporate Cash Management and/or Payment’s businessBachelor’s degree in engineering/technology with relevant work experienceUnderstanding of AML and terrorist financing trends and typologiesKnowledge of and experience with the latest AML transaction monitoring technologyExperience of working on AML Transaction Monitoring product implementations, such as Actimize and Mantas; preferably modern transaction monitoring systems leveraging machine learning algorithms for detectionHands-on experience developing, tuning, and validating ML models (e.g., XGBoost, Random Forest, Clustering)Strong knowledge of databases, SQL scripts and querying large data setsExperience with Data Lake, Data Bricks, Tableau, Excel and/or other data analytics/visualization toolsAbility to deal with data models and work on mapping data across platformsExcellent organization and project management skills – ability to execute and manage a project independentlyExcellent written and verbal communication skills, ability to adapt to new changes and new challenges
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Source: Goldman Sachs careers