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- Tasks: Lead the development of credit risk analytics solutions for consumer lending.
- Company: Join a rapidly expanding financial services company making waves in the industry.
- Benefits: Enjoy opportunities for growth and innovation in a dynamic work environment.
- Why this job: Be at the forefront of credit risk modelling and make impactful decisions.
- Qualifications: Degree in Data Science, Statistics, or related field; experience with large datasets essential.
- Other info: Work independently and present findings to stakeholders in a fast-paced setting.
The predicted salary is between 43200 - 72000 £ per year.
This rapidly expanding financial services company is seeking a Lead Credit Risk Analyst to join their Consumer Lending function. Working with the Commercial Director, you will develop credit risk analytics solutions to enhance Credit Scoring and Lending decision-making to optimise and grow their loan portfolio.
Key Responsibilities:
- Developing and implementing advanced statistical models and preferably machine learning algorithms 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, Excel and SQL proficiency (Essential)
- Degree in relevant subject (Data Science, Statistics, Computer Science, Economics or similar degree) (Essential)
- Strong proficiency in programming languages such as Python, R (Preferable)
- Experience using Salesforce and data visualisation tools (Preferable)
- Strong presentation skills, including the ability to translate complex data into understandable insight.
- A great attention to detail and be process-oriented to review, suggest and implement improvements where appropriate.
- Able to work in a fast-paced, changing environment.
Job Offer:
- Opportunity to develop and enhance credit risk modelling and analytics strategy.
- Opportunity to join a rapidly expanding financial services company.
Lead 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 Lead Credit Risk Analyst - Consumer Lending/Loans
✨Tip Number 1
Familiarise yourself with the latest trends in credit risk analytics and machine learning. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Network with professionals in the financial services industry, especially those who work in credit risk. Attend relevant conferences or webinars to make connections and gain insights that could be beneficial for your application.
✨Tip Number 3
Prepare to showcase your analytical skills by working on a personal project or case study related to credit risk modelling. This will not only enhance your understanding but also provide you with concrete examples to discuss during interviews.
✨Tip Number 4
Brush up on your presentation skills, as you'll need to convey complex data insights clearly. Practising how to present your findings to non-technical stakeholders can set you apart from other candidates.
We think you need these skills to ace Lead Credit Risk Analyst - Consumer Lending/Loans
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in the financial services industry, particularly in credit risk analysis. Emphasise your proficiency with large datasets, Excel, SQL, and any programming languages like Python or R.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about credit risk analytics and how your skills align with the company's goals. Mention specific projects or experiences that demonstrate your ability to develop and implement statistical models.
Showcase Your Analytical Skills: Provide examples of how you've used data analysis to inform business decisions. Discuss any experience with A/B testing or predictive modelling, as these are key responsibilities for the role.
Prepare for Interviews: If invited for an interview, be ready to discuss your analytical approach and how you present complex data insights. Prepare to answer questions about your experience with credit risk models and your ability to work in a fast-paced environment.
How to prepare for a job interview at Michael Page Technology
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with developing and implementing statistical models. Highlight specific examples where you've used data analysis to inform business decisions, especially in credit risk or lending.
✨Demonstrate Technical Proficiency
Make sure to mention your proficiency in Excel, SQL, and any programming languages like Python or R. Be ready to explain how you've used these tools in past roles to handle large datasets and perform complex analyses.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think of examples where you had to analyse trends or conduct A/B testing to evaluate credit strategies, and be ready to discuss the outcomes.
✨Communicate Clearly and Concisely
Since strong presentation skills are essential, practice explaining complex data insights in a straightforward manner. Use visuals if possible, and ensure you can convey your findings effectively to stakeholders who may not have a technical background.
