SoftNice
Lead Risk Model Specialist – Financial Crime Prevention Models
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Role Summary
We are looking for an experienced Lead Developer to own the development, validation, and governance of transaction monitoring models within a Financial Crime Prevention / AML function for a major Nordic banking client.
This role combines deep model risk expertise with hands-on analytical work, balancing rigor and practical constraints while driving model governance forward within the Transaction Monitoring Unit (TMU).
Key Responsibilities
- Own the development and validation of transaction monitoring models, with a focus on model documentation, model review, and model governance
- Drive model governance activities within TMU, including validation assessments and implementation of 2nd line feedback
- Set and execute the direction for model development and experimental design, finding the right balance between analytical rigor and practical constraints
- Document model design and outcomes, iterating with the analytics team to ensure accuracy, completeness and analysis of model assumptions, limitations and weaknesses
- Provide hands-on support for prototyping tests and analytical methodologies
- Mentor, uplift and collaborate within the analytics team to design, test, and implement model SOPs (e.g. data lineage/governance, tuning and calibration, monitoring of model operations and outcomes)
- Represent the organisation with a high degree of professionalism in collaboration with external and internal stakeholders
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Required Skills and Experience
- Extensive experience in model risk management, model governance, and validation
- Strong background in data science, statistics and quantitative methods
- Experience in academic or technical writing, particularly in the context of model documentation
- Advanced degree in a quantitative field, e.g. Computer Science, Actuarial Science, Statistics, Mathematics, or equivalent
- Strong analytical and problem-solving skills
- Excellent communication, presentation and stakeholder management skills
- Organised, structured and professional, able to take initiative and work proactively under own direction
- Assertive communication with the ability to set direction and achieve results in a dynamic, changing environment
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Nice to Have
- Experience in Financial Crime/AML, e.g. transaction monitoring and technology suppliers
- Transaction monitoring platforms such as Quantexa
- Experience as a model validator or quantitative risk analyst
Required skills
- Statistical Modelling
- Risk Management
- Finance
- modelling
- Data Science
- Transaction monitoring
- AML
- Model Validation
- Transaction
Preferred skills
- Banking
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