Compliance Sr. Manager - Data Governance/ AML/Sanctions Data Steward

Job Description

At FIS, our technology and our people are moving forward. We advance the way the world pays, banks and invests. We believe in building inclusive, diverse teams. Together, we innovate to help our colleagues, clients and communities succeed. If you’re ready to grow your career and make an impact in fintech, we have one question: Are you FIS?
 

About the role: 

We’re seeking a data-driven Compliance Senior Manager to lead the design, optimization, and governance of AML transaction monitoring across the FIS enterprise. In this role within the 2nd line Corporate Compliance function, you will be responsible for reviewing, challenging, and validating the soundness of AML transaction monitoring and data architecture across the first line function. To achieve this, you will provide subject matter guidance on model development and tuning methodology.  

You will document, monitor, and report on 1st line AML program health and model performance by driving metrics and KPIs implementation, to Compliance leadership and other key stakeholders. You will also participate in financial crimes tech and data strategy and business plan development and regularly interact with executives.  

About the team:

The team you will be joining plays an important role in maintaining AML tech and data compliance for the FIS enterprise and maintaining our customers’ trust. To be successful we need your experience to help navigate a complex organization and strive for cutting-edge solutions that enable AML robustness and scalability. You will help with building resilience and produce deliverables day to day.  

What you will be doing:
A key aspect of the role is to present and demonstrate soundness of the AML transaction monitoring program tooling and architecture as well as support of sanctions screening tools to senior stakeholders across Compliance 

• Foster confidence in the accuracy and effectiveness of models and processes through continuous challenge and ongoing monitoring, leveraging advanced analytics and machine learning techniques  

• Apply quantitative and statistical skills in challenging models to support financial crimes risk mitigation while enabling the business  

• Implement data strategies to identify anomalies and develop risk mitigation plans  

• Engage in AML typology assessment and transaction monitoring rules development by leading data assessments to identify workflow and monitoring gaps   

• Leverage strong AML compliance business skills to identify data gaps and develop insights and trends to determine program maturity against the risk appetite 

• Act as an AML data steward to translate qualitative AML risks into quantitative metrics and KPIs by developing dashboards 

What you will need:
Bachelor’s degree in quantitative discipline, such as Mathematics/Statistics, Business Analytics, Data Science, Information Systems, or related field 

• Preferred: Master’s degree in data science/information systems or the equivalent combination of education, training, or work experience 

• 8+ years of experience with BSA AML Compliance, USA PATRIOT ACT, familiarity with international financial crimes related regulations requirements, AML transaction monitoring rules development, testing, tuning and model validation  

• 8+ years of experience in data management and analytics, data governance, data architecture, and data modeling 

• 5+ years of experience leading teams and building positive business partner relationships  

• Strong hands-on experience leveraging SQL, Python, R for data analytics and Machine Learning required 

• Experience with building Agentic/AI workflows leveraging LLMs and SLMs preferred  

• Proficiency with AML transaction monitoring systems such as Actimize, Unit 21, SAS, and data platforms and dashboarding tools such as Databricks, Snowflake, Tableau, PowerBI and related database tools and technologies preferred  

• Excellent verbal and written communication and collaboration skills to effectively communicate with both business and technical