Job Description
Job Title
Quantitative Engineer
Location
Berlin, Bucharest, UK
Start Date
April 2026
Summary
We are seeking analytical and data-driven Quantitative Engineers to develop and validate advanced statistical and machine learning models supporting client onboarding and portfolio risk monitoring. The role involves analysing large datasets to assess credit, payments, and financial crime risks, and enabling automated, AI-driven decisioning across the client life cycle. Strong quantitative, programming, and financial risk domain expertise is required.
Experience
Candidates should have a strong quantitative background in Mathematics, Statistics, Data Science, or a related field, with proven experience developing and validating statistical, stochastic, or machine learning models for financial risk. Proficiency in Python, SQL, and modern data processing frameworks is essential. Applicants should demonstrate domain expertise in credit risk, payments risk, or anti-financial crime modelling, ideally gained within banking, fintech, or other risk-intensive environments, including exposure to portfolio risk assessment and model life cycle management.
Qualifications
- Degree in Mathematics, Statistics, Data Science, Quantitative Finance, or a related quantitative field.
- Proven experience developing and validating statistical or machine learning models within financial risk (eg credit, payments, or anti-financial crime).
- Proficiency in Python, SQL, and working with large datasets and modern data platforms.
- Understanding of model life cycle management and portfolio-level risk assessment.
- Experience in banking, fintech, or other regulated, risk-intensive environments is desirable.
Key Responsibilities
Model Development & Validation
- Design, develop, validate, and back-test predictive models covering credit risk, payments risk and transactional behaviour, anti-financial crime indicators, and external market or event-driven risks.
- Build robust statistical models to accurately capture portfolio risk exposures.
- Evaluate model performance, predictive strength, and resilience using historical data and stress-testing scenarios.
- Analyse large and complex datasets to identify patterns, uncover vulnerabilities, and anticipate emerging risks.
Risk Domain Expertise
- Demonstrate sound knowledge of credit risk modelling, payments risk, and anti-financial crime frameworks.
- Develop rating models leveraging multivariate data, including transactional activity, financial statements, and external market factors.
- Assess clients' repayment capacity through quantitative analysis of financial and non-financial indicators.
Cross-Functional Collaboration
- Partner closely with risk subject matter experts, business analysts, and engineering teams to ensure model development aligns with business objectives.
- Present methodologies, findings, and risk insights clearly to both technical and non-technical stakeholders.
Competencies and Skills Required
- Strong quantitative background in Mathematics, Statistics, Data Science, or related discipline.
- Demonstrable hands-on experience developing statistical, stochastic, or machine-learning models within a risk context.
- Proficiency in Python, SQL, or comparable analytical programming languages.
- Experience working with modern data processing and data engineering frameworks.
- Domain expertise in at least one of the following areas: credit risk, payments risk, or anti-financial crime/fraud detection.
- Experience across the full model life cycle, including development, validation, implementation, and ongoing performance monitoring.
- Exposure to portfolio-level financial risk assessment and risk aggregation methodologies.
- Familiarity with the development of rating models utilising publicly available financial disclosures and market data.
- Previous experience within banking, fintech, or other highly regulated, risk-intensive environments.
- Strong analytical and research skills.
- Excellent communication and writing skills for marketing and presentations.
- Organisational skills to manage multiple tasks effectively.
- Proficiency in Microsoft 365 or Google Productivity tools
- Ability to work both independently and within a team.
- Demonstrated leadership abilities, including the ability to take ownership and getting things done.
- Excellent written and verbal communication skills, with the ability to convey complex information in a clear and concise manner.
- Ability to collect, organize, analyse, and disseminate significant amounts of information with attention to detail.
About Us
Crear Group Ltd is a management consultancy focused on business transformation and growth. We help public and private sector organisations deliver complex change, streamline operations, and use data to improve decision-making. From strategy to delivery, we enable better customer outcomes, higher efficiency, lower costs, and sustainable results.