Senior Credit Risk Analyst (Lead) - Consumer Lending

Nottingham
1 week ago
Create job alert

This rapidly expanding financial services company are seeking a Senior Credit Risk Analyst to join their Consumer Lending function. Working with the Commercial Director you will develop credit risk analytics / scorecard modelling solutions to enhance Credit Scoring & Lending decisioning to optimise and grow their loan portfolio

Client Details

Rapidly expanding financial services company

Description

This rapidly expanding financial services company are seeking a Senior Credit Risk Analyst to join their Consumer Lending function. Working with the Commercial Director you will develop credit risk analytics / scorecard modelling solutions to enhance Credit Scoring & Lending decisioning to optimise and grow their loan portfolio.

Key Responsibilities:

Developing and implementing advanced statistical / scorecard models to predict credit risk, optimise credit scoring, and enhance decision-making/underwriting processes.
Develop and maintain predictive models to assess credit risk and forecast customer behaviour.
Analyse large datasets to identify trends, patterns, and insights that inform business decisions.
Perform data cleaning to ensure high-quality data for analysis,
Conduct A/B testing and other experiments to evaluate the impact of credit strategies and policies.
Develop credit risk models, such as probability of default (PD) using various modelling techniques.
Working independently and presenting findings and recommendations to stakeholders in a clear and concise manner.Key Skills / Experience:

Experience in the Financial Services Industry (Essential)
Experience working with large data sets (Essential)
Proficiency in Python, R, SQL or other programming languages (Essential)
Proficiency in Excel (Essential)
Strong presentation skills, including the ability to translate complex data into understandable insight (Essential)
A great attention to detail and be process-oriented to review, suggest and implement improvements where appropriate. (Essential)
Able to work in a fast paced, changing environment.(Essential)
Degree in relevant subject (Data Science, Statistics, Computer Science, Economics or similar degree) (Preferable)
Experience using Salesforce and data visualisation tools (Preferable)Profile

Experience in the Financial Services Industry (Essential)
Experience working with large data sets (Essential)
Proficiency in Python, R, SQL or other programming languages (Essential)
Proficiency in Excel (Essential)
Strong presentation skills, including the ability to translate complex data into understandable insight (Essential)
A great attention to detail and be process-oriented to review, suggest and implement improvements where appropriate. (Essential)
Able to work in a fast paced, changing environment.(Essential)
Degree in relevant subject (Data Science, Statistics, Computer Science, Economics or similar degree) (Preferable)
Experience using Salesforce and data visualisation tools (Preferable)Job Offer

Opportunity to develop and enhance credit risk modelling & analytics strategy

Opportunity to join a rapidly expanding financial services company

Related Jobs

View all jobs

Manager - Credit Analytics

Manager - Credit Analytics

Private Equity Real Estate Analyst

Senior Applications Engineer

Senior Pricing Manager

Senior Pricing Manager

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Data Science Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Data science has become a linchpin in modern business, transforming oceans of raw data into actionable insights that guide strategy, product development, and personalised customer experiences. With this surge in data-centric operations, the need for effective data science leadership has never been more critical. Guiding a team of data scientists, analysts, and machine learning engineers requires not only technical acumen but also the ability to foster collaboration, champion ethical practices, and align complex modelling efforts with overarching business goals. This article provides practical guidance for managers and aspiring leaders aiming to excel in data-driven environments. By exploring strategies to motivate data science professionals, develop mentoring frameworks, and set achievable milestones, you will be better prepared to steer your team towards meaningful, evidence-based outcomes.

10 Essential Books to Read to Nail Your Data Science Career in the UK

Data science continues to be one of the most exciting and rapidly evolving fields in tech. With industries across the UK—ranging from finance and healthcare to e-commerce and government—embracing data-driven decision-making, the demand for skilled data scientists has soared. Whether you're a recent graduate looking for your first role or a professional aiming to advance your career, staying updated through books is crucial. In this article, we explore ten essential books every data science job seeker in the UK should read. Each book provides valuable insights into core concepts, practical applications, and industry-standard tools, helping you build skills employers are actively looking for.

Navigating Data Science Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Data science has taken centre stage in the modern workplace. Organisations rely on data-driven insights to shape everything from product innovation and customer experience to operational efficiency and strategic planning. As a result, there is a growing need for skilled data scientists who can analyse large volumes of data, build predictive models, communicate findings effectively, and collaborate cross-functionally. If you are looking to accelerate your data science career—or even land your first role—attending data science career fairs can be a game-changer. Unlike traditional online applications, face-to-face interactions let you showcase your personality, passion, and communication skills in addition to your technical expertise. However, to stand out in a busy environment, you need a clear strategy: from polishing your personal pitch and asking thoughtful questions to following up with a memorable message. In this article, we’ll guide you through every step of making a strong impression at data science career fairs in the UK and beyond.