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- Tasks: Build and enhance statistical models for credit decisioning and risk management.
- Company: Join RSM, a leading global audit and consulting firm with big ambitions.
- Benefits: Flexible working, 26 days holiday, study support, and wellness benefits.
- Why this job: Make a real impact in a dynamic team while developing your skills.
- Qualifications: 3+ years in credit risk modelling; proficiency in Python, SQL, and data visualisation tools.
- Other info: Diverse and inclusive culture that values unique perspectives.
The predicted salary is between 36000 - 60000 £ per year.
As one of the world's largest networks of audit, tax and consulting firms, RSM delivers big ideas and premium service to help middle-market businesses thrive. We are a fast-growing firm with big ambitions and a clear goal to become the premium adviser to the middle market, globally. This vision motivates us to improve every day. If you are looking for a firm where you can build a future and make an impact, then RSM is the place for you.
We’re looking for a hands-on Assistant Manager, with a minimum of 3 years’ experience, to join our Quantitative Analytics & Risk Modelling team in London to build, validate, and enhance statistical and machine learning models that drive credit decisioning, portfolio monitoring, capital computation, and impairment forecasting. You’ll partner with Risk, Product, and Data teams to ship robust models from development into production, with clear governance and documentation.
Responsibilities
- Delivering models that raise approval quality and reduce bad debt without stifling growth
- Enhancing IRB capital estimates and IFRS 9 ECL accuracy, improving RWA efficiency and P&L predictability
- Streamlining analytics pipelines, cutting time-to-insight and enabling faster product iterations
- Establishing clear monitoring and early-warning indicators, reducing model risk and surprise losses
- Producing audit-ready documentation and evidence, lowering supervisory findings and remediation costs
What we are looking for
- Bachelor’s or Master’s in Statistics, Mathematics, Econometrics, Data Science, Computer Science, or related field
- Minimum of 3 years in credit risk modelling/analytics within a bank, lender, or consulting firm
- Exposure to Python, SAS, SQL, R and dashboarding in Power Bi or Tableau
- Solid understanding of PD/LGD/EAD, IFRS 9 impairment, and Basel III/IV IRB concepts
- Experience with segmentation, curing/roll rates, delinquency/collections strategies, and provisioning mechanics
- Ability to translate complex model behaviour into business-friendly narratives and visuals and to frame hypotheses, design robust experiments, and explain results succinctly
What we can offer you
- Study Support (FRM, CFA)
- Hybrid and Flexible working
- 26 Days Holiday (with the option of purchasing additional days)
- Lifestyle, Health, and Wellbeing including financial wellbeing benefits such as financial tools, electric car scheme and access to a virtual GP.
- Access to a suite of 300+ courses on demand developed by our inhouse Talent Development team.
Diversity and Inclusion at RSM
At RSM, we want to create a strong sense of belonging so that people of all identities, backgrounds, and cultures feel they can bring their true self to work. Our clients come from all walks of life. We aim to achieve that same diversity of background, experience and perspective in our own teams, so that we can genuinely understand our client's needs. Diverse teams bring a broader range of ideas and insights to work. That’s why we’re working together to ensure our firm’s principles and processes support a firm culture that embraces difference and strengthens inclusion.
Assistant Manager - Quantitative Analytics & Risk Modelling employer: RSM
Contact Detail:
RSM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Assistant Manager - Quantitative Analytics & Risk Modelling
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with RSM employees on LinkedIn. Building relationships can open doors that applications alone can't.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in quantitative analytics. We want you to showcase your expertise and how it aligns with RSM's goals.
✨Tip Number 3
Don’t just talk about your experience; bring it to life with examples! Use the STAR method (Situation, Task, Action, Result) to clearly demonstrate how you've made an impact in previous roles.
✨Tip Number 4
Apply through our website for a smoother process! It shows you're genuinely interested in joining RSM and gives us a chance to see your application in the best light.
We think you need these skills to ace Assistant Manager - Quantitative Analytics & Risk Modelling
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your quantitative analytics and risk modelling experience, especially any work with credit risk models. We want to see how you can make an impact at RSM!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about this role and how your background aligns with our goals. Be sure to mention your experience with Python, SAS, SQL, or any relevant tools.
Showcase Your Achievements: When detailing your past roles, focus on specific achievements that demonstrate your ability to deliver results. Whether it's improving model accuracy or streamlining processes, we love to see quantifiable impacts!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at RSM
✨Know Your Models Inside Out
Make sure you can discuss the statistical and machine learning models you've worked on in detail. Be prepared to explain how they drive credit decisioning and enhance capital computation. This shows your hands-on experience and understanding of the role.
✨Brush Up on Technical Skills
Since the job requires exposure to Python, SAS, SQL, R, and dashboarding tools like Power BI or Tableau, ensure you're comfortable discussing your proficiency in these areas. You might even want to prepare a quick demo or example of your work with these tools.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about past experiences where you enhanced model accuracy or streamlined analytics pipelines, and be ready to share those stories with clear outcomes.
✨Communicate Complex Ideas Simply
Practice translating complex model behaviours into business-friendly narratives. The interviewers will want to see if you can frame hypotheses and explain results succinctly, so think of ways to simplify your explanations without losing the essence of your work.
