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- direct hands-on experience with Anti Money Laundering Transaction Monitoring Models (Actimize, Mantas, FICO Tonbeller, NORKOM, Google AML (DRA) or similar)
- experience in rule-based scenario tuning, development and enhancements
- proficient in one or more scripting languages - SQL, R, MatLab, SAS, Python - with Python being the advantage, including data manipulation libraries (Pandas, NumPy), data visualization (Matplotlib, Seaborn, Plotly, PyPlot). PySpark knowledge is a strong advantage.
- ensure UBS model development documentation standards are strictly followed regarding model data inputs, model design and execution, and model use and ongoing performance monitoring
- will be the primary liaison officer for senior management and stakeholders including model validation, business, and regulatory and Audit partners concerning inquiries related to transaction monitoring models supported by the individual contributors being recruited for these roles
- actively contribute to the Book of Work planning & Model Validation activity lifecycle by delivering model specific tasks on time, in budget, and in scope
- experience in understanding the red flag guidance provided by the regulatory bodies and come up with different risk modeling option and further optimize transaction monitoring models
- experience in interpreting transaction monitoring related data across different line of businesses such as correspondent banking, investment banking, traditional banking services etc.
- good understanding and experience of end-to-end model lifecycle
- knowledge in Machine Learning and AI principles or hands-on experience is an advantage
- ability to create unit tests in Python (PyTest library) come as an advantage
UBS RecruitingYour teamYou'll be joining the GCRG Methodologies and Models, the model and innovation hub for UBS non-financial risk management. You'll play a driving role in ensuring our models comply with our global model risk governance framework and will shape the continuous improvement of the models and the overall function.Your expertise
- an advanced University degree (Master or Ph.D.) in STEM (computer science, natural science, math, statistics, physics, economics, data science, electrical or mechanical engineering, financial engineering, or related domain.)
- ideally 5+ years of quantitative model development or model validation experience in financial services, risk & compliance domain with strong domain knowledge in Financial Crime Prevention, Market Surveillance, Transaction Monitoring, Financial Crime Compliance and experience in how these risks can effectively be monitored using models, including scenario optimization and testing methodologies such as Below The Line (BTL) testing
- strong analytical mindset with the ability to identify risks and opportunities including the ability to analyze data to bridge business purpose, and vice versa
- relevant, hands-on experience and understanding of model risk management / model governance requirements and processes. Role requires thorough understanding of model regulatory framework and ability to support and guide model owners and steer the portfolio of UBS transaction monitoring models efficiently and effectively
- self-starter, able to manage and prioritize multiple priorities, including the ability to independently define/design, document, and defend conceptual soundness, outcomes analysis, identify boundary conditions, weaknesses and limitations, and production of high quality of model documentation
- excellent project management, communication & presentation skills with strong focus in soft/interpersonal skills. This includes end to end project ownership, manages critical path of delivery timelines, mitigates blockers, and escalates as needed, avoids delivery surprises by managing timelines, expectations, and managing escalations early and proactively while avoiding surprises for all project stakeholders such as Financial Crime Prevention, IT, Model Validation, Business Partners, Regulatory Relations, and senior executives
- high proficiency and fluency in verbal and written English required
- the ideal candidate will also have relevant first-hand experience either supporting designated individuals or representing large financial organizations in a regulatory review setting with various regulators articulating either model development or model validation activities and attributing appropriateness of model construct and key modelling decisions from first line or second line perspective, preferably with relevant regulatory remediation experience
- candidates with Credit Risk, Market Risk, or Operational Risk quant experience, ML/AI in either model development or model validation will also be considered for these roles
- AML-relevant certifications come as an advantage (CAMS, CFA, FRM, FCICP or similar)