Credit Risk Analyst – SME (m/f/d)

Pliant GmbH • London, CA

42d • Hybrid

About The Position

As Credit Risk Analyst – SME (d/f/m), you will be responsible for building and optimizing automated credit strategies for small and medium-sized enterprises (‘SME’). While a strong foundation in credit risk is essential, you’ll bring hands-on coding expertise to directly work with data pipelines, API integrations, decision engines, with the option to branch into model building (PD, LGD, EAD, EL). You drive initiatives to achieve project targets. You deliver efficiency improvement to the teams. You continuously support the evolution of our tech stack towards automated decision making. You foster data-driven decision making. You align credit risk strategies with business goals. If that is you, then join us and work closely with the Director for Credit Risk Management and the VP of Credit. This position sits directly in the functional domain with exposure to business and responsibility for the common achievement of goals. This role will be based in London (hybrid).

Requirements

• Degree in a quantitative or engineering discipline or related field.
• 3–5 years of experience in risk modelling, quantitative analytics, financial engineering or similar domain
• Good understanding of credit risk strategies for unsecured SME exposures; familiarity with open banking data and transaction-level insights is a plus.
• Strong data analysis and engineering capabilities, SQL and Python is essential. Command of statistical modeling software is a plus.
• Experience in working with APIs, decision engines, as well as data aggregation and orchestration services is a strong plus.
• Experienced in agile development, and ability to own and drive cross-functional projects.
• Determination and desire to work in a team to achieve high-quality results for our customers, even under stress.
• Fluent in English; additional European languages are a plus.

Responsibilities

• Credit strategy: Design, develop, test and calibrate automated credit risk strategies and continuously improve them based on empirical tests. Implement monitoring processes. Design and build early warning systems.
• Loss models: At a later stage, build PD, LGD, EAD, EL models.
• Portfolio: Analyze portfolio performance, identify risk drivers and mitigation strategies based on empirical data or feature engineering.
• Efficiency: Build dashboard for insights. Measure and monitor process efficiency, identify bottlenecks and blockers in workflows and resolve them together with the team.
• Process automation: Continuously review and enhance operational processes to reduce handling times while keeping quality within agreed parameters. Build E2E data pipelines using SQL, Python and decision engines.
• Collaboration: Partner with Risk Management, Data and Engineering teams to build E2E data processes together. Manage cross-functional projects.
• Communication: Facilitate smooth and fact-based information flow between your colleagues. Support data-driven decision making within the credit risk domain. Support the development of a culture of open dialogue, which is focused on mutual respect and the joint achievement of excellent results.

Benefits

• The opportunity to work in a growing team with big responsibilities that thrives on a strong exchange of knowledge and excellence
• Attractive remuneration
• Flat hierarchy and transparent communication in a relaxed, professional atmosphere
• Opportunity to develop your talent in a dynamic team with ambitious goals
• Flexibility and possibility to work remotely
• Company card with a monthly allowance for lunches, coffee, etc. with co-workers

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 101-250 employees