Act as a key point of contact between FCC and IT for day‑to‑day ownership of sanctions screening models
Monitor model performance, thresholds, and tuning parameters; identify emerging issues and partner with technology teams on remediation
Support data quality, list management, and model configuration activities related to sanctions screening
Oversee ongoing monitoring of model outputs, including alert volumes, risk distribution, and operational impacts driven by business growth and regulatory changes
Lead and/or support sanctions model upgrades, enhancements, and periodic recalibrations across enterprise screening platforms
Perform technical design and review of sanctions models
Evaluate and enhance the use of advanced modeling techniques, including machine learning and natural language processing (NLP)
Conduct tuning analysis and validation testing
Execute Model Risk Management (MRM) calendar activities
Apply advanced data analysis techniques to assess model effectiveness, risk coverage, and operational impacts
Develop repeatable analytical tools and scripts (preferably in Python and SQL)
Assess and support entity resolution techniques
Draft, update, and maintain high‑quality MRM documentation
Lead MRM engagements to completion

Requirements

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, Finance, or a related quantitative or technical discipline
6+ years of experience in financial crime compliance, sanctions screening, data science, quantitative analytics, or model risk management within a regulated financial services environment
Demonstrated experience designing, reviewing, validating, or operating sanctions screening applications & models, including responsibility for model performance, tuning, and ongoing monitoring
Strong quantitative and analytical skill set with deep, hands‑on proficiency in at least one advanced analytics or modeling discipline, including machine learning, natural language processing (NLP), or entity resolution techniques, or alternatively statistical analysis, model validation, and quantitative risk assessment
Proficiency in Python and SQL for data analysis, model evaluation, and automation of repeatable analytical processes, with demonstrated proficiency in at least one analytical or data science platform or package (e.g., Databricks, pandas, NumPy, scikit‑learn, or equivalent tools)
Experience working with modern analytical tools and cloud‑based data environments, including relational and distributed data stores, with the ability to analyze large, complex datasets to assess model effectiveness, alert quality, risk coverage, and operational impacts
Strong understanding of model risk management principles, including model lifecycle governance, validation, documentation, and regulatory interaction
Experience preparing clear, well‑structured technical and governance documentation and presenting analytical findings to senior stakeholders.

Benefits

Permanent contract from day one
Additional holidays (Birthday Day Off, 3rd and 5th year anniversary Day Off)
Gold Medical Package for employees and their families (partner and children)
Premium life insurance package and private pension plan
Wide range of soft skills training, technical workshops, language classes and development programs
Opportunities to volunteer your time to company-driven initiatives, employee networks or organizations of your choice
Variety of well-being programs

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningnatural language processingdata analysismodel validationquantitative risk assessmententity resolutionmodel performance tuninganalytical tools developmentstatistical analysismodel risk management

Soft Skills

quantitative skillsanalytical skillscommunication skillsleadershipdocumentation skillsproblem-solvingcollaborationattention to detailorganizational skillspresentation skills