Credit Risk Architect

Stott and May; Knutsford; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading recruitment agency seeks a Credit Risk Architect to shape technology strategies for creditworthiness assessments in Knutsford. The ideal candidate has deep expertise in decision engine platforms and a strong understanding of financial risk and compliance. This role requires collaboration with data science teams to ensure scalable and efficient lending decisions, offering a competitive day rate of £552.50.

Qualifications

• Deep expertise in decision engine platforms like FICO Blaze or Pega.
• Strong programming skills in Python, R, or SAS.
• Proficient in data warehousing environments.
• Understanding of AWS, Azure, or GCP for scalable solutions.
• Advanced knowledge of statistical modeling and machine learning.
• In-depth understanding of lending risk principles.
• Knowledge of regulatory frameworks and credit policy.

Responsibilities

• Architect end-to-end credit risk decisioning and affordability systems.
• Design decision engines integrating internal and external data.
• Translate credit policy into technical requirements.
• Partner with data science teams for model integration.
• Ensure compliance with lending regulations.
• Establish performance monitoring frameworks.
• Drive automation across the credit lifecycle.
• Act as a subject-matter expert for risk and technology.

Skills

Decision engine platforms expertise (e.g. FICO Blaze, Pega)

Data analytics and programming (Python, R, SAS)

Enterprise system integration

Cloud platforms understanding (AWS, Azure, GCP)

Statistical modelling & machine learning knowledge

Credit lifecycle understanding

Regulatory frameworks knowledge

Job description

Credit Risk Architect

Location: Knutsford (must live within one hour or be willing to relocate)
Day Rate: £552.50 per day (Inside IR35)
Onsite Requirement: 2–3 days per week (non-consecutive)

Overview

We are seeking a Credit Risk Decisioning & Affordability Architect to shape the technology strategy and architecture that underpins creditworthiness assessment and lending decisions. This role is critical to developing intelligent, automated credit decisioning platforms that bring together data, analytics, regulatory compliance, and enterprise architecture.

You will design the overall lending decision architecture, working closely with risk teams, data scientists, and senior stakeholders to build systems that ensure efficient, fair, and compliant lending outcomes.

Key Responsibilities

• Architect end-to-end credit risk decisioning and affordability systems
• Design and implement decision engines, integrating internal and external data sources
• Translate credit policy and business objectives into technical requirements and rule frameworks
• Partner with data science teams to integrate statistical and machine learning models
• Ensure compliance with lending regulations and deliver full audit transparency
• Establish performance monitoring frameworks — approval rates, default trends, model accuracy
• Drive automation across the credit lifecycle to reduce manual intervention and increase efficiency
• Act as a subject‑matter expert across risk, technology, and senior leadership teams

Required Skills & Experience

• Deep expertise in decision engine platforms — e.g. FICO Blaze, Pega, or similar
• Strong data analytics and programming capability (Python, R, SAS)
• Proficient in enterprise system integration and data warehousing environments
• Understanding of cloud platforms (AWS, Azure, GCP) for scalable decisioning
• Advanced knowledge of statistical modelling & machine learning techniques
• In‑depth understanding of credit lifecycle, affordability, and lending risk principles
• Knowledge of credit policy, underwriting criteria, affordability metrics, and regulatory frameworks

Who We’re Looking For

A highly analytical, technically strong architect with deep financial risk understanding, capable of bridging business strategy and technical design. You will bring clarity, precision, and innovation to credit decisioning, ensuring solutions are compliant, scalable, and operationally robust.