Risk Analytics & Modeling Lead

Qualco Technology

Senior Risk professional creating and improving credit risk models for fintech organization. Overseeing analytics and regulatory compliance across credit lifecycle in innovative digital landscape.

Posted 7/1/2026full-timeAthens • 🇬🇷 GreeceSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing credit risk models, including machine learning classifiers and decision frameworks, while ensuring compliance with EU regulatory standards. Proficient in translating complex models into production-ready systems and conducting thorough portfolio analytics.

Highest-signal resume keywords

Credit Risk AnalyticsMachine Learning MethodsEU Regulatory FrameworksSQL and Python/R ProficiencyModel Risk Management

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Hard Skills

Credit Risk ModelsDecision TreesTime-Series ForecastingModel Performance MonitoringData ExtractionFeature EngineeringLoan MechanicsRisk SystemsAutomated DecisioningBacktesting

Soft Skills

Structured ThinkingStrong Business JudgmentRisk AwarenessIndependent OperationAgile Team Collaboration

Tools & Technologies

Decision EnginesData PipelinesLoan Origination SystemsAutomated Decision-Making SystemsPortfolio Monitoring Tools

Industry Keywords

EBA GuidelinesIFRS 9GDPR ComplianceEmbedded FinanceBNPLConsumer Credit RegulationsModel GovernanceStress TestingThin-File UnderwritingReal-Time Decisioning

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Develop and own credit risk models, including scorecards, decision trees, and machine learning classifiers (e.g. PD, LGD, EAD estimation aligned with CRR/CRD expectations where applicable);
Build and maintain time-series models for portfolio monitoring, early warning signals, and stress testing (EBA Guidelines on stress testing & IRB where relevant);
Translate models into production-ready decisioning logic (rules, cut-offs, segmentation) within loan origination and servicing systems;
Design and refine underwriting policies, ensuring alignment with EBA Guidelines on Loan Origination & Monitoring and consumer credit regulations;
Conduct portfolio analytics, backtesting, and model performance monitoring (discrimination, calibration, stability, fairness considerations);
Support regulatory compliance (model governance, documentation, audit trails, explainability, GDPR considerations in automated decision-making);
Collaborate with product, engineering, and data teams to embed risk logic into customer journeys across online and merchant channels;
Operate in a hands-on capacity, directly executing analyses, model builds, and implementations in a lean team environment;
Ensure that all activities and duties are carried out in full compliance with regulatory requirements and supporting the continued implementation of the Group Anti-Bribery and Corruption Policy.

Requirements

What you’ll need

7+ years in credit risk analytics, modeling, or quantitative risk within banking, fintech, or consumer finance;
Strong experience with both:
- Deterministic / rule-based decision frameworks (scorecards, policy rules);
- Machine learning methods for classification and time-series forecasting;
Deep understanding of loan mechanics (amortization, pricing, delinquency, recoveries) and unsecured lending products;
Proven experience with risk systems (LOS, decision engines, data pipelines) and translating models into production;
Solid knowledge of EU regulatory frameworks, including:
- EBA Guidelines on Loan Origination & Monitoring;
- Model risk management expectations (ECB/TRIM principles where relevant);
- IFRS 9 impairment concepts;
- GDPR implications for automated decisioning;
Strong data skills (SQL, Python/R; experience with large datasets and feature engineering);
Ability to operate independently and deliver end-to-end (from data extraction to model deployment).
Highly hands-on; comfortable executing detailed analytical work despite seniority;
Structured thinker with strong business judgment and risk awareness;
Able to balance model sophistication with explainability and regulatory expectations;
Thrives in small, agile teams with evolving processes.
Experience in embedded finance / BNPL / merchant-integrated lending;
Exposure to real-time decisioning systems;
Familiarity with alternative data and thin-file underwriting.

Benefits

Comp & perks

Competitive compensation, Meal vouchers, and annual bonus programs.
Cutting-edge IT equipment, mobile phone, and data plan.
Modern facilities, free coffee, beverages, indoor parking, and in-house restaurant.
Private health insurance, occupational doctor, workplace counselor and nutritionist.
Onsite gym, wellness facilities, and ping pong room.
Career and talent development tools.
Mentoring, coaching, personalized annual learning, and development plan.
Employee referral bonus, regular wellbeing, ESG, and volunteering activities.