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For Companies At a Glance
- Tasks: Develop credit risk models and analyse large datasets to optimise lending decisions.
- Company: Join a rapidly expanding financial services company making waves in consumer lending.
- Benefits: Enjoy opportunities for growth, remote work options, and a dynamic work environment.
- Why this job: Be part of a team that shapes the future of credit scoring and lending strategies.
- Qualifications: Experience in financial services and proficiency in Python, R, SQL, and Excel required.
- Other info: Ideal for those who thrive in fast-paced environments and love data-driven decision-making.
The predicted salary is between 43200 - 72000 £ per year.
This rapidly expanding financial services company is 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 and 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.
- Work independently and present 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)
Job Offer:
- Opportunity to develop and enhance credit risk modelling and analytics strategy
- Opportunity to join a rapidly expanding financial services company
Senior Credit Risk Analyst - Consumer Lending/Loans employer: Michael Page Technology
Contact Detail:
Michael Page Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Credit Risk Analyst - Consumer Lending/Loans
✨Tip Number 1
Familiarise yourself with the latest trends in credit risk analytics and scorecard modelling. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the financial services industry, especially those who work in credit risk. Attend relevant webinars or local meetups to build connections that could lead to referrals or insider information about the company.
✨Tip Number 3
Brush up on your programming skills, particularly in Python, R, and SQL. Consider working on personal projects or contributing to open-source projects that showcase your ability to handle large datasets and develop predictive models.
✨Tip Number 4
Prepare to discuss your analytical approach and how you've used data to drive business decisions in past roles. Be ready to present case studies or examples that highlight your problem-solving skills and attention to detail.
We think you need these skills to ace Senior Credit Risk Analyst - Consumer Lending/Loans
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in the financial services industry, particularly with large datasets and credit risk analytics. Use specific examples that demonstrate your proficiency in Python, R, SQL, and Excel.
Craft a Compelling Cover Letter: In your cover letter, explain why you are interested in the Senior Credit Risk Analyst position. Discuss your relevant skills and experiences, particularly in developing statistical models and presenting findings to stakeholders.
Showcase Your Analytical Skills: When detailing your previous roles, focus on your ability to analyse data and identify trends. Mention any specific projects where you developed predictive models or conducted A/B testing to enhance decision-making processes.
Highlight Attention to Detail: Emphasise your attention to detail and process-oriented mindset in your application. Provide examples of how you've reviewed and improved processes in past roles, especially in fast-paced environments.
How to prepare for a job interview at Michael Page Technology
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in programming languages like Python, R, and SQL during the interview. Be prepared to discuss specific projects where you've used these skills to analyse large datasets or develop predictive models.
✨Prepare for Data Analysis Questions
Expect questions that assess your ability to analyse data and identify trends. Brush up on your statistical knowledge and be ready to explain how you would approach a real-world credit risk scenario using data analysis.
✨Demonstrate Strong Presentation Skills
Since the role requires presenting findings to stakeholders, practice explaining complex data insights in a clear and concise manner. Use examples from your past experiences to illustrate how you've successfully communicated data-driven recommendations.
✨Emphasise Attention to Detail
Given the importance of accuracy in credit risk analysis, be prepared to discuss how you ensure high-quality data and thorough analysis. Share examples of how your attention to detail has led to successful outcomes in previous roles.
