At a Glance
- Tasks: Develop and implement quantitative models for structured credit while performing data analysis.
- Company: Join Marsh, a leading firm in the financial services industry.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Work in a dynamic environment with excellent career advancement opportunities.
- Why this job: Make an impact in finance by enhancing modelling frameworks and collaborating with experts.
- Qualifications: Proficiency in Python is essential; experience with NumPy, pandas, and SQL is a plus.
The predicted salary is between 60000 - 80000 £ per year.
Marsh in London is seeking a highly motivated Structured Credit Quantitative Analyst to join our team. The role is based in London and operates on a hybrid model with at least three days in the office.
You will support development and implementation of quantitative models for structured credit, perform data analysis, and collaborate with senior colleagues to enhance modelling frameworks and reporting. Proficiency in Python is essential, with experience in NumPy, pandas and SQL a plus.
#J-18808-LjbffrHybrid Structured Credit Quant Analyst – 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 Hybrid Structured Credit Quant Analyst – London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Marsh!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Hybrid Structured Credit Quant Analyst – London at Marsh.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Marsh.
✨Apply Directly through Our Website
When you find a suitable opening like Hybrid Structured Credit Quant Analyst – London at Marsh, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Marsh, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Marsh. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Marsh
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Marsh!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
