At a Glance
- Tasks: Develop and implement quantitative models for structured credit products and support risk assessment.
- Company: Join Guy Carpenter, a leader in the financial services industry with a collaborative culture.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Diverse and inclusive workplace with excellent career development opportunities.
- Why this job: Kickstart your career in quantitative finance and make an impact in structured credit analysis.
- Qualifications: Degree in a quantitative field and proficiency in Python programming required.
The predicted salary is between 30000 - 40000 £ 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 requires working at least three days a week in the office.
What you can expect
- 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 Num Py, pandas, Sci Py, 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 make 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.
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 .
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.
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Structured Credit Quantitative Analyst (Entry/Graduate level considered) in London employer: Marsh
Marsh is an excellent employer that fosters a dynamic work culture in the vibrant locations of Plymouth and Newquay, offering employees the chance to thrive in a supportive environment. With a strong emphasis on professional development and growth opportunities, team members are encouraged to enhance their skills while contributing to meaningful client relationships. The company also values resilience and ambition, making it an ideal place for those looking to make a significant impact in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Structured Credit Quantitative Analyst (Entry/Graduate level considered) in London
✨Get Involved with Campus Finance Societies
Join your university's finance or investment society — they're a goldmine for networking, guest lectures, and career fairs. These societies often host employers looking for entry-level talent like you, so get involved and make yourself known!
✨Attend Industry Workshops and Webinars
Look for workshops and webinars focused on banking and financial services. These events not only boost your knowledge but also let you connect with industry professionals who could help you land that entry-level role at places like Marsh.
✨Leverage LinkedIn for Informational Interviews
Take advantage of LinkedIn to reach out to professionals working in banking, especially those who've started in entry-level positions. Politely ask for a quick chat about their experience and any advice they might have on breaking into the field.
✨Apply Directly through Company Websites
Don't just rely on job boards. Head directly to Marsh's careers page and look for their entry-level openings. They might have opportunities that aren’t advertised widely, so keep checking back for new listings!
We think you need these skills to ace Structured Credit Quantitative Analyst (Entry/Graduate level considered) in London
Some tips for your application 🫡
Splash Your Skills on Your CV:In the banking and financial services realm, it's all about numbers and analysis. Make sure to highlight any relevant coursework, internships, or projects where you've used skills like financial modelling, data analysis, or risk assessment. Show us you can crunch those numbers!
Educational Achievements Matter:For an entry-level role, your grades and academic accomplishments are key. If you have any certifications, like CFA Level 1 or something similar, don’t forget to include them. We love seeing ambition and commitment to the industry, so flaunt those achievements!
Craft a Personal Touch in Your Cover Letter:Your cover letter is your chance to show us your enthusiasm for banking and finance! Share why you're passionate about the industry and how your studies or previous experiences have prepared you for this role. We want to see that spark and motivation!
Use the Right Format and Language:In banking, clarity is king. Use a clean, professional format for your CV and cover letter. Make sure to avoid jargon, but don’t shy away from technical terms where appropriate – just keep it all clear and easy to read. Let’s see your professionalism shine through!
How to prepare for a job interview at Marsh
✨Brush Up on Your Financial Knowledge
Since you're diving into the banking and financial services industry, make sure you're up to speed with current market trends and financial concepts. Be prepared to discuss things like interest rates and investment strategies, as you might get some technical questions that gauge your understanding.
✨Show Off Your Analytical Skills
Analytical skills are key in banking, so be ready to showcase how you've used them in your studies or any relevant projects. Prepare to tackle case studies or hypothetical financial scenarios during the interview that require you to analyse data and make informed decisions.
✨Demonstrate Your Team Spirit
As this is an entry-level role, they’ll likely look for how well you can collaborate and fit into their team. Think of examples from group projects or internships where you successfully worked with others. It'll help show that you're keen to learn and grow in a team-oriented environment.
✨Prepare Thoughtful Questions
Approach your interview with curiosity! Prepare insightful questions that reflect your knowledge of the industry, such as asking about the latest technology being implemented in their services. It shows you're genuinely interested in the company's operations and future.
