Financial Crime Model Validation Lead
£700pd – £800pd Inside IR35
Remote in UK
Initial 6 months
emagine is a high-end professional services consultancy and solutions firm specialising in providing business and technology services to the financial services sector, we power progress, solve challenges and deliver real results through tailored high-end consulting services and solutions.
We are seeking an experienced Financial Crime Model Validation Lead to play a critical role in the governance, validation, assurance and deployment of Financial Crime technology models and solutions, including Transaction Monitoring, Screening, Customer Risk Rating and Quantexa platforms.
Acting as the central coordination point throughout the model life cycle, you will ensure robust governance, validation and risk management frameworks are established and maintained in line with business and regulatory requirements.
You will ensure full traceability of model development and validation activities, documenting the end-to-end rationale behind model decisions, including methodology, assumptions, supporting evidence and validation outcomes.
Key Responsibilities
Lead and coordinate model validation activities across the full model life cycle.
Ensure robust governance, risk management and validation frameworks are implemented, maintained and continuously improved.
Independently challenge model methodologies, assumptions, outputs, thresholds, segmentation approaches and risk factor selection.
Work closely with Data Scientists, Developers, Model Risk, Compliance and business stakeholders to validate model design, implementation and performance.
Establish and maintain complete model traceability, ensuring transparency of decisions, assumptions and outcomes.
Document the “what, why and how” behind model development, validation findings, recommendations and implementation decisions.
Produce comprehensive validation reports covering model performance, effectiveness, risk considerations, data dependencies and implementation rationale.
Identify gaps, risks, control weaknesses and areas for improvement across models, data, processes and documentation.
Define and monitor validation progress, ensuring issues, actions and remediation activities are tracked through to completion.
Support stakeholders in making informed, risk-based decisions by balancing regulatory requirements, model effectiveness, delivery timelines and operational needs.
Drive accountability across multiple teams and workstreams, ensuring validation activities remain on track.
Support regulatory reviews, internal audits, model governance forums and independent assurance exercises where required.
Required Experience & Skills
Model Validation & Governance
Experience leading or supporting model validation activities within a regulated Financial Services environment.
Strong understanding of model governance, model risk management and validation frameworks.
Experience validating Transaction Monitoring, Name Screening, Payment Screening, Sanctions Screening, Customer Risk Rating (CRR), Fraud or Risk models.
Experience conducting model tuning, calibration, threshold optimisation and effectiveness assessments.
Demonstrable experience producing high-quality validation, governance and regulatory documentation.
Ability to define, measure and monitor validation progress, including issue management and remediation tracking.
Understanding of end-to-end model governance requirements, including documentation standards, auditability and traceability.
Financial Crime & Regulatory Experience
Experience working within AML, Financial Crime Compliance, Fraud, Transaction Monitoring or Sanctions environments.
Strong understanding of regulatory expectations relating to Financial Crime systems and controls.
Experience supporting regulatory remediation activities, independent reviews, skilled person reviews, internal audit findings or assurance engagements is highly desirable.
Understanding of Financial Crime typologies, risk assessments and customer risk rating methodologies.
Data & Analytical Experience
Strong understanding of data quality, data lineage and source-to-model traceability.
Experience assessing the impact of data quality on model performance and effectiveness.
Ability to challenge and validate analytical methodologies, model assumptions and performance outcomes.
Experience validating rules-based, analytical, machine learning or AI-enabled models would be advantageous.
emagine is an equal opportunity employer, and employment practices are based strictly on merit. It is the policy of the Company to give equal opportunity in employment regardless of sex, sexual orientation, marital status, race, age, disability, gender reassignment, pregnancy and maternity, religion or ethnic origin
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