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For Companies At a Glance
- Tasks: Develop credit risk analytics and scorecard models to optimize lending decisions.
- Company: Join a rapidly expanding financial services company making waves in consumer lending.
- Benefits: Gain valuable experience in a fast-paced environment with opportunities for growth.
- Why this job: Be at the forefront of credit risk innovation and make impactful business decisions.
- Qualifications: Experience in financial services and proficiency in Python, R, SQL, or similar is essential.
- Other info: Ideal for data enthusiasts looking to shape the future of lending.
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 & Lending decisioning to optimise and grow their loan portfolio.
Client Details
Rapidly expanding financial services company.
Description
This role involves developing credit risk analytics/scorecard modelling solutions to enhance Credit Scoring & Lending decisioning to optimise and grow the loan portfolio.
Key Responsibilities:
- Develop and implement 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)
- 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)
Job 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 Technology
Contact Detail:
Michael Page Technology 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. Highlight specific projects or roles where you developed credit risk models or worked with large datasets, as this is essential for the Senior Credit Risk Analyst position.
✨Tip Number 2
Familiarize yourself with the latest trends in credit risk analytics and scorecard modelling. Being able to discuss recent developments or methodologies during your interview will demonstrate your passion and expertise in the field.
✨Tip Number 3
Prepare to discuss your proficiency in programming languages like Python, R, or SQL. Be ready to provide examples of how you've used these tools to analyze data or develop predictive models in previous roles.
✨Tip Number 4
Practice translating complex data insights into clear, concise presentations. This role requires strong presentation skills, so being able to effectively communicate your findings 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 analytics and scorecard modelling.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience in the financial services industry, particularly with large datasets and statistical modelling. Use specific examples to demonstrate your proficiency in Python, R, SQL, and Excel.
Showcase Your Analytical Skills: Provide examples of how you've developed predictive models or conducted data analysis in previous roles. Highlight any A/B testing or experiments you've performed that relate to credit strategies.
Prepare a Strong Cover Letter: Craft a cover letter that not only outlines your qualifications but also conveys your enthusiasm for the role. Discuss how you can contribute to enhancing credit scoring and lending decision-making processes.
How to prepare for a job interview at Michael Page Technology
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages like Python, R, and SQL. Highlight specific projects where you've developed credit risk models or worked with large datasets, as this will demonstrate your technical proficiency.
✨Prepare for Data Analysis Questions
Expect questions that assess your ability to analyze data and identify trends. Be ready to explain your approach to data cleaning and how you ensure high-quality data for analysis, as this is crucial for the role.
✨Demonstrate Strong Presentation Skills
Since you'll need to present 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 effectively communicated data-driven recommendations.
✨Understand the Business Context
Research the company and its consumer lending function. Familiarize yourself with their credit scoring processes and any recent developments in the financial services industry that may impact their business decisions. This knowledge will help you align your answers with their goals.
