Manager, Model Validation
Scotiabank
Requisition ID: 246471
Employee Referral Program – Potential Reward: $0.00
We are committed to investing in our employees and helping you continue your career at ScotiaGBS
Purpose
The Global Model Risk Management area provides independent and consistent model validation and approval across various risk types, including market risk, retail/non-retail credit risk, operational risk, capital models, Anti Money Laundering (AML) and other key risk/financial models.
The manager provides support to the Senior Manager in the validation of models and strategies, which may include Canadian and International retail/non-retail credit adjudication and behavior, credit retail strategies, AML, Fraud, or Market Risk Capital. This position entitles activities related to model validation work including data management and model quality assurance testing/validation to establish overall soundness of the risk measurement, delivery of various ad-hoc validation assignments, collaboration with the model development teams and business lines, and communicating results to model owners ensuring compliance with internal framework and regulatory requirements. He/she may also communicate and negotiate with the different counterparties regarding issues identified during the validation.
Accountabilities
(Applicable across Credit Risk, AML/Financial Crime, Fraud and Market & Counterparty Risk Capital)
• Plan and execute validations (supporting the Senior Manager/Director and/or independently) for models and strategies across one or more risk domains, which may include:
Retail/non‑retail credit adjudication and behaviour, retail credit strategies (adjudication, behaviour, collections), AML models (e.g., transaction monitoring, customer/client risk rating, screening), Fraud, market risk and counterparty credit risk capital models, stress testing, and trade surveillance.
• Define the validation scope and framework for each assignment, including objectives, uses/limitations, regulatory context, testing strategy, success criteria, and materiality thresholds.
• Perform detailed quantitative and technical assessments, including:
o Data: input data quality, lineage, representativeness, stability, and bias assessment.
o Conceptual soundness: model design, assumptions, segmentation, variable selection/feature engineering, and reasonableness of methodology.
o Implementation verification: code/configuration review, architecture and control assessment (versioning, access, change management), and benchmark/replication testing.
o Performance testing: discrimination, calibration, stability/PSI, back‑testing, sensitivity/what‑if analysis, stress/scenario analysis, and (where relevant) P&L attribution/CCR exposure checks or AML detection efficacy.
• Execute independent calculations and programming to reproduce and analyze model behaviour and performance; design and automate validation tests and analytics as appropriate.
• Formulate clear recommendations to remediate issues and enhance models, data pipelines, implementation controls, monitoring, and/or development processes; assess materiality and prioritize actions.
• Produce and maintain validation deliverables: draft/final validation reports, issue logs, model risk ratings, executive summaries, workpapers, and supporting documentation; ensure accuracy, traceability, and completeness for independent review.
• Communicate findings effectively to stakeholders (model owners, developers, business, risk, technology, audit), present conclusions, negotiate remediation plans/timelines, and maintain collaborative relationships throughout the validation lifecycle.
• Governance and compliance: operate in alignment with internal Model Risk Management policies, standards, and applicable regulatory/supervisory expectations (e.g., SR 11‑7, OSFI/BCBS guidance, AMLD/FATF), as relevant to the model’s domain and jurisdiction.
• Inventory & lifecycle management: support keeping the model inventory current; track validation schedules, approvals, issue statuses, conditions, and periodic review requirements.
• Methodology advancement and standardization: research and develop new validation techniques, enhance test libraries, templates, and frameworks, and align practices with evolving industry standards.
• Continuous monitoring support: advise on performance metrics, thresholds, alerts/triggers, change‑impact assessments, and annual/periodic reviews.
• Stakeholder management and risk culture: build strong relationships with key contacts for each validation, promote a sound model risk culture, and drive constructive challenge.
Education / Experience / Other Information
Experience:
• 1+ year of experience in the development, validation, or performance assessment of Market Risk or Counterparty Credit Risk models (e.g., VaR, Expected Shortfall, sensitivities‑based measures, exposure models).
• Experience in Market Risk Management, including knowledge of Value‑at‑Risk (VaR) methodologies (historical simulation, parametric, Monte Carlo), back-testing, stress testing, and understanding of market risk factor behavior.
• Familiarity with major trading products and their risk drivers, including Interest Rates (IR), Foreign Exchange (FX), Equities, and Commodities, as well as related derivatives.
• 2+ years of experience in independent model validation, including assessment of conceptual soundness, technical testing, benchmarking, and performance monitoring across quantitative risk models.
Required Functional (Technical) Competencies:
• Degree in fields such as Mathematics, Statistics, Econometrics, Physics, Computer Science, Financial Mathematics, Financial Engineering (Master or above, Ph.D. Preferred); Industry certification or credentials will be an asset (e.g. CFA, FRM).
• Knowledges of the derivative pricing model theory, market risk capital modeling, and market data. Experience in market risk modeling including the valuation and capital models, or counterparty credit risk modeling.
• Strong knowledge of statistical and mathematical techniques and proven ability to employ these to analyze large sets of data.
• Proficient computing skills and grasp of programming languages such as Python, R, MATLAB (Open Sources). Ability to adapt to various programming languages and environments.
• Excellent verbal and written communication skills. Excellent written and presentation skills to provide advices, explanations and communications to various users and stakeholders.
• Familiar with concepts, structures, pros and cons, and various aspects of machine learning (ML) and AI models
• Ability to speak and write in English is required.
Working Conditions
- Work in a standard office-based environment; non-standard hours are a common occurrence.
Location(s): Colombia : Bogota : Bogota
Scotia GBS is a Scotiabank Group company located in Bogota, Colombia created to support different processes of the Bank and the development and execution of its global services strategy in 15 countries in the Americas. It is composed of 7 service units. We offer an inclusive, positive work environment, and competitive benefits.
At ScotiaGBS, we value the unique skills and experiences each individual brings to the Bank and are committed to creating and maintaining an inclusive and accessible environment for everyone. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at ScotiaGBS; however, only those candidates who are selected for an interview will be contacted.