Risk Analytics Lead (Líder de Analítica de Riesgo) - Hybrid
Clara is looking for a Risk Analytics Lead to own the analytical engine of our Risk function globally. This role sits within the Risk team and is responsible for three interconnected domains: building and maintaining the risk models and scorecards that power credit decisions across our markets; owning Clara's Model Risk Management (MRM) framework; and acting as the Risk team's lead designer for our risk data infrastructure, working hand-in-hand with the Data team on its implementation.
This is a high-impact, cross-functional role for someone who combines deep technical expertise in risk modeling with the judgment to govern model risk and the communication skills to bridge Risk, Data, and senior leadership.
What you'll do
Risk Modeling
Design, develop, and maintain the full suite of risk models across the credit lifecycle — scorecards, probability of default (PD), loss given default (LGD), exposure at default (EAD), expected credit loss (ECL), and behavioral models
Own model backtesting, performance monitoring, and recalibration processes; ensure models remain fit for purpose as portfolio composition and macroeconomic conditions evolve
Develop and maintain early warning indicators, portfolio segmentation, and concentration risk analytics
Translate model outputs into actionable credit strategy inputs for Credit Policy and Portfolio Management teams
Model Risk Management (MRM)
Design and own Clara's MRM framework: model inventory, model risk classification, validation standards, and model risk appetite
Define and enforce model governance processes — development standards, independent validation, approval workflows, and ongoing review cadences
Act as internal challenger on all risk models; ensure models are documented, explainable, and auditable
Establish thresholds for model risk escalation and lead remediation when models breach performance benchmarks
Risk Data Infrastructure (Design)
Partner with the Data Engineering team as the Risk domain expert and architecture co-designer for the risk data infrastructure
Define business and analytical requirements for risk data pipelines, feature stores, and reporting layers; ensure the infrastructure supports both real-time decisioning and portfolio analytics needs
Drive adoption of robust data standards within the Risk function — lineage, quality controls, and documentation
Translate Risk's analytical roadmap into concrete data infrastructure requirements; prioritize with the Data team based on business impact
Leadership & Stakeholder Management
Build and manage a lean, high-performing Risk Analytics team; define hiring needs and grow the function as Clara scales
Work closely with Credit Policy, Credit Desk, Portfolio Management, and Compliance — act as the technical partner that turns risk strategy into quantified models
Present model performance, MRM status, and analytical insights to senior leadership and, when relevant, to regulators
Champion a data-driven culture within Risk; define standards for analytical rigor and model documentation across the team
Who you are
Must haves
Academic background in Statistics, Mathematics, Actuarial Science, Engineering, Economics, or a related quantitative field
7+ years of experience in credit risk analytics, with hands-on ownership of the full model lifecycle — from development and validation to production monitoring and recalibration
Demonstrated experience building or managing a Model Risk Management framework (model inventory, validation governance, model risk appetite)
Deep proficiency in Python or R for modeling, and SQL for data extraction and analysis
Experience translating model requirements into data infrastructure needs; comfortable working alongside data engineers as a domain expert and co-designer
Strong grasp of credit risk regulation in at least one of Clara's markets (CNBV/Mexico, SFC/Colombia, BACEN/Brazil)
Proven ability to communicate technical concepts clearly to non-technical stakeholders, including executive leadership
Fluency in English and Spanish (Portuguese a strong plus)
Nice to haves
Experience in B2B credit or working capital products (trade credit, credit lines, commercial cards)
Familiarity with fintech or high-growth startup environments where you've had to build infrastructure and processes from scratch
Exposure to audit processes, regulatory reporting, and model-related regulatory examinations
Experience building or managing small analytics or data science teams
Hands-on experience with MLOps tooling, model monitoring platforms, or feature stores
Knowledge of Basel credit risk frameworks (IRB approaches, ECL under IFRS 9)