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For Companies At a Glance
- Tasks: Lead credit risk analytics and develop scorecard models for consumer lending.
- Company: Join a rapidly expanding financial services company making waves in the industry.
- Benefits: Gain hands-on experience with advanced analytics and work in a dynamic environment.
- Why this job: Shape the future of lending decisions while enhancing your analytical skills.
- Qualifications: Experience in financial services and proficiency in Python, R, SQL, and Excel required.
- Other info: Ideal for those who thrive in fast-paced settings and love data-driven decision-making.
The predicted salary is between 43200 - 72000 £ per year.
- Opportunity to develop and enhance credit risk modelling & analytics strategy
- Opportunity to join a rapidly expanding financial services company
About Our Client
Rapidly expanding financial services company
Job Description
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 & 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 insights (Essential)
- Great attention to detail and 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)
The Successful Applicant:
- 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 insights (Essential)
- Great attention to detail and 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)
What’s on Offer:
Opportunity to develop and enhance credit risk modelling & analytics strategy.
Opportunity to join a rapidly expanding financial services company.
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Senior Credit Risk Analyst (Lead) - Consumer Lending employer: Michael Page (UK)
Contact Detail:
Michael Page (UK) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Credit Risk Analyst (Lead) - Consumer Lending
✨Tip Number 1
Make sure to showcase your experience in the Financial Services Industry during the interview. Prepare specific examples of how you've successfully developed credit risk models or worked with large datasets, as this will demonstrate your expertise and relevance for the role.
✨Tip Number 2
Brush up on your programming skills, especially in Python, R, and SQL. Be ready to discuss how you've used these languages in past projects, particularly in developing predictive models or conducting data analysis.
✨Tip Number 3
Prepare to present complex data insights clearly and concisely. Practice explaining your findings from previous analyses to someone without a technical background, as strong presentation skills are essential for this role.
✨Tip Number 4
Familiarize yourself with A/B testing methodologies and be ready to discuss any relevant experiences. Understanding how to evaluate the impact of credit strategies will set you apart from other candidates.
We think you need these skills to ace Senior Credit Risk Analyst (Lead) - Consumer Lending
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description. Understand the key responsibilities and required skills, especially focusing on credit risk modelling and analytics.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience in the financial services industry and your proficiency with large datasets. Mention specific projects where you developed statistical models or worked with programming languages like Python or R.
Showcase Your Skills: Make sure to highlight your strong presentation skills and attention to detail. Provide examples of how you've translated complex data into understandable insights in previous roles.
Tailor Your Application: Customize your application materials to reflect the company's focus on credit risk analytics. Use keywords from the job description to ensure your application stands out to hiring managers.
How to prepare for a job interview at Michael Page (UK)
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python, R, SQL, and Excel during the interview. Be prepared to discuss specific projects where you utilized these skills to develop credit risk models or analyze large datasets.
✨Prepare for Data Analysis Questions
Expect questions that assess your ability to analyze large datasets and identify trends. Brush up on your statistical knowledge and be ready to explain how you would approach data cleaning and model development.
✨Demonstrate Strong Presentation Skills
Since strong presentation skills are essential, practice explaining complex data insights in a clear and concise manner. You might be asked to present a past project, so think about how you can effectively communicate your findings to stakeholders.
✨Emphasize Attention to Detail
Be prepared to discuss how you ensure high-quality data for analysis and how you review processes for improvements. Providing examples of your attention to detail in previous roles will help demonstrate your fit for this position.
