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Allica Bank is the UK's fastest-growing fintech firm, focused on serving established SMEs—a major underserved segment representing over a third of the UK economy.
The Modelling team sits within Credit Portfolio Management and is central to building measurement and decisioning models for Allica's lending products. You will work on two critical model suites: IFRS9 impairment models (PD, LGD, SICR, economic response) that measure credit risk and support auditor/investor reporting, and decisioning models and policy rules that power automated lending and drive fast, consistent credit decisions.
In this hands-on role, you will take models and decisioning changes from problem definition through data identification, cleansing, analysis, model development, implementation, and ongoing monitoring. You will move fluidly between structured model development and fast-paced ad-hoc analysis, collaborating closely with Finance, Credit Risk, Underwriting, Collections, Product, Data, Engineering, Capital Markets, and Model Risk teams. You will communicate complex concepts clearly to stakeholders with varying technical expertise and work with third-party suppliers as needed.
Key responsibilities include:
- Design, build, implement, and continuously refine the bank's credit risk models across IFRS9 impairment and automated lending decisioning suites
- Develop and deploy models in Python across the full lifecycle: data preparation, feature engineering, model fitting, validation, implementation, and performance assessment
- Perform ad-hoc analysis to optimize credit policy rules and decisioning flows using rule-firing, decision, and outcome data
- Produce regular monitoring reports covering population stability, discriminatory power, calibration, segment/vintage performance, decision rates, and underwriting alignment
- Recalibrate or redevelop models as portfolio experience matures, comparing predicted vs. actual outcomes and adjusting scaling, score cut-offs, or policy thresholds
- Lead root-cause investigations into model, rule, or decisioning-flow underperformance by tracing issues through decision logs, data lineage, feature calculations, production pipelines, and implementation logic
- Build well-controlled, reproducible modelling processes and drive improvements to data, tooling, and infrastructure
- Document models, rules, assumptions, limitations, and changes to high standards, supporting governance, independent review, validation, and stakeholder engagement
- Work closely with cross-functional teams to track model requirements and translate business needs into practical solutions while maintaining strong internal controls
Allica Bank offers flexible and hybrid working arrangements, full onboarding support, continued development opportunities, pension contributions, discretionary bonus, private health cover, life assurance, and family-friendly policies including enhanced maternity and paternity leave.
REQUIREMENTS:
- Minimum 5 years' hands-on risk modelling experience applying statistical techniques (logistic regression, linear regression) and machine learning models to solve practical business problems
- Comfort with large datasets and data extraction/manipulation using Excel, SQL, Python, and BI tools
- Proven track record with Python coding; comfortable using GenAI tools to increase coding productivity
- Good understanding of IFRS9, credit, and lending concepts, preferably in commercial lending
- Self-motivated, driven, and passionate about building great solutions
- Ability to work independently and adapt quickly to changing priorities in a dynamic environment
- Strong stakeholder collaboration and teamwork skills
- Strong technical and business-focused writing skills
- Experience implementing models into software applications is highly desirable
The posting notes that prior experience in this area matters, but encourages applications from strong candidates who may not meet every requirement.
