Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Senior Credit Risk Manager

Nottingham
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst – Fraud Analytics

Data Scientist - Borrow Analytics Manager

Data Scientist - Borrow Analytics Manager

Wholesale Credit Risk Management - Senior Data Engineer - Executive Director

Wholesale Credit Risk Product & Data Analyst - VP - Belfast

Senior Data Engineer

SENIOR CREDIT RISK MANAGER
UP TO £90,000
FULL TIME, PERMANENT
NOTTINGHAM CITY CENTRE

SF Recruitment are recruiting a Senior Credit Risk Manager for their client based in Nottingham City Centre. You will play a pivotal role in shaping and leading our clients credit risk strategies. This is a high-impact position, responsible for driving portfolio performance, ensuring compliance, and supporting the business's continued growth through data-led decision-making.

Key Responsibilities

  • Lead the design, implementation, and optimisation of credit risk strategies across acquisition, account management, and decisioning.
  • Manage and mentor a high-performing credit risk team, fostering a culture of development and excellence.
  • Partner with cross-functional teams including Product, Technology, Compliance, and Finance to ensure risk strategies align with business objectives.
  • Own and continuously enhance the credit risk policy framework, decisioning models, and governance to ensure regulatory compliance and audit readiness.
  • Deliver actionable portfolio performance insights and risk analytics to executive leadership.
  • Develop and maintain statistical models (e.g., PD models, bureau and custom scorecards) to support credit underwriting and segmentation.
  • Leverage credit bureau data (e.g., TransUnion, Experian) to inform and refine credit strategies.
  • Conduct robust exploratory data analysis and ensure data integrity through rigorous data cleaning processes.
  • Design and oversee A/B testing to evaluate and optimise credit risk strategies.
  • Translate complex analytical insights into clear recommendations for stakeholders.
  • Balance commercial objectives with risk appetite, optimising scorecards and policies for profitable, sustainable growth.

    Essential Requirements:
  • A degree in Data Science, Statistics, Economics, or a related field
  • Minimum of 8 years' experience in the Financial Services sector
  • Strong experience working with large and complex data sets
  • Proficiency in programming languages such as Python, R, or SQL
  • Advanced skills in Excel
  • Excellent communication skills, with the ability to present complex technical concepts to non-technical audiences
  • Highly analytical, detail-oriented, and committed to continuous improvement
  • Comfortable operating in a dynamic and fast-paced environment

    Desirable:
  • Experience working with credit bureau data
  • Familiarity with Salesforce and data visualisation tools (e.g., Tableau, Power BI)

    What's on Offer:
  • 25 days annual leave plus Bank Holidays
  • Flexible and hybrid working options
  • Long-term career progression in a growing, mission-driven company
  • Private healthcare

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.