At a Glance
- Tasks: Develop and implement quantitative models for structured credit analysis.
- Company: Join Guy Carpenter, a leader in risk and reinsurance, based in London.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Diverse and inclusive workplace with excellent career development opportunities.
- Why this job: Make an impact in finance while learning from top specialists in a collaborative environment.
- Qualifications: Degree in a quantitative field and proficiency in Python programming.
The predicted salary is between 30000 - 40000 ÂŁ per year.
We are seeking a highly motivated and analytically skilled Structured Credit Quantitative Analyst to join our team at Guy Carpenter. This role will be based in London. This is a hybrid role that has a requirement of working at least three days a week in the office.
This early-career role is ideal for recent graduates or professionals who have a strong foundation in quantitative disciplines and programming. The successful candidate will support the development and implementation of quantitative models to analyse structured credit products and contribute to risk assessment and portfolio management.
We will count on you to:
- Develop, validate, and implement quantitative models for structured credit products
- Perform data analysis and statistical modelling to support credit risk assessment and pricing
- Collaborate with senior quantitative analysts to enhance modelling frameworks and improve decision-making processes
- Write clean, efficient, and well-documented code primarily in Python to automate data processing, model implementation, and reporting
- Conduct research on market trends, credit performance, and new modelling techniques relevant to structured credit
- Assist in preparing presentations and reports for internal stakeholders and external clients
What you need to have:
- Bachelor’s or Master’s degree in a quantitative discipline such as Mathematics, Physics, Computer Science, Engineering, Statistics, or a related field
- Relevant experience, including internships or academic projects involving quantitative analysis or programming
- Proficiency in Python programming, including experience with libraries such as NumPy, pandas, SciPy, or similar
- Familiarity with basic version control tools such as Git
- Strong analytical and problem-solving skills with attention to detail
- Basic understanding of fixed income markets and structured credit products is a plus but not required
- Ability to work collaboratively in a team environment
- Self-motivated with a strong desire to learn and grow in the field of quantitative finance and structured credit
What makes you stand out:
- Experience with data visualization tools (e.g., Matplotlib, Seaborn)
- Familiarity with SQL or other database querying languages
- Exposure to risk management frameworks or financial modeling software
At Guy Carpenter, a Marsh business, you can be your best. We work on challenges that matter with colleagues who help bring out our best. Our uniquely collaborative environment will empower you to focus on your personal and professional success, learning from top specialists in the (re)insurance industry and leading you towards a rewarding and impactful career.
Guy Carpenter is a business of Marsh (NYSE: MRSH), a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective.
Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, civil partnership status, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. We are an equal opportunities employer. We are committed to providing reasonable adjustments in accordance with applicable law to any candidate with a disability to allow them to fully participate in the recruitment process. If you have a disability that may require reasonable adjustments, please contact us at reasonableaccommodations@mmc.com.
Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.
Structured Credit Quantitative Analyst (Entry/Graduate level considered) in London employer: Marsh McLennan
Contact Detail:
Marsh McLennan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Structured Credit Quantitative Analyst (Entry/Graduate level considered) in London
✨Tip Number 1
Network like a pro! Reach out to alumni from your university or connections in the finance industry. A friendly chat can lead to valuable insights and even job referrals.
✨Tip Number 2
Show off your skills! Create a GitHub repository with your coding projects, especially those using Python. This gives potential employers a peek into your abilities and problem-solving approach.
✨Tip Number 3
Prepare for interviews by brushing up on quantitative concepts and coding challenges. Practice common interview questions related to structured credit and be ready to discuss your past projects.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, you’ll find all the latest opportunities right there.
We think you need these skills to ace Structured Credit Quantitative Analyst (Entry/Graduate level considered) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Structured Credit Quantitative Analyst role. Highlight your quantitative skills, programming experience, and any relevant projects or internships. We want to see how your background fits with what we're looking for!
Show Off Your Python Skills: Since Python is key for this role, don’t forget to showcase your coding abilities. Include specific examples of projects where you used Python, especially with libraries like NumPy or pandas. This will help us see your practical experience in action!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about structured credit and how your skills align with our needs. Keep it concise but engaging – we love a good story that connects your journey to our mission.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy and ensures your application goes directly to us. Plus, you’ll find all the details you need about the role right there!
How to prepare for a job interview at Marsh McLennan
✨Know Your Quantitative Stuff
Brush up on your quantitative skills and be ready to discuss any relevant projects or coursework. Make sure you can explain complex concepts in simple terms, as this shows your understanding and ability to communicate effectively.
✨Python Proficiency is Key
Since the role requires Python programming, practice writing clean and efficient code. Be prepared to showcase your experience with libraries like NumPy and pandas, and maybe even solve a coding challenge during the interview.
✨Research the Company and Role
Familiarise yourself with Guy Carpenter and their work in structured credit. Understanding their business model and recent market trends will help you answer questions more confidently and show your genuine interest in the role.
✨Prepare for Team Collaboration Questions
As teamwork is crucial in this role, think of examples from your past experiences where you successfully collaborated with others. Highlight your ability to work in a team and how you contribute to a positive working environment.