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- Tasks: Join our Market Data Analytics Team to analyze and model financial risk data.
- Company: Be part of a renowned Investment Bank with a focus on financial markets.
- Benefits: Enjoy a stable, long-term role with opportunities for growth and impact.
- Why this job: Make a lasting impact in a high-priority area while working with a dedicated team.
- Qualifications: Statistical background, experience with market data, Python, SQL, and strong quantitative skills required.
- Other info: Apply by December 23, 2024, and showcase your problem-solving and communication skills.
The predicted salary is between 36000 - 60000 £ per year.
We’re hiring for a high-priority position within the Market Data Analytics Team at a well-known Investment Bank .
This role sits in the Traded Risk Management department, which includes market risk, product control, and counterparty credit risk and is an exciting opportunity that offers a stable, long-term role where your expertise will have a lasting impact.
You’ll contribute to a dedicated team responsible for overseeing market data sourcing, transformations, modeling, and proxies .
The team supports the broader Financial Markets and Group Treasury functions across all asset classes, with a particular focus on Interest Rate Derivatives and Commodities .
What We’re Looking For:-
The ideal candidate will have a statistical and mathematical background and have worked in a similar role, now looking to gain further exposure within a high-priority area.
In order to apply your experience will include:-
- Project management, analysis, and visualization of large market data sets.
- Market Risk with a solid understanding of derivatives pricing.
- Traders and Structurers are also encouraged to apply.
Essential Experience / Knowledge:
- Experience with and a keen interest in financial markets’ policies, guidelines, and regulations .
- Proven ability to handle large market data sets and associated technologies.
- Python programming skills, particularly for building solutions with large datasets.
- SQL experience and strong quantitative knowledge of several asset classes, their risks, and pricing.
- A deep understanding of market risk metrics (e.g., VaR, HVaR, IRC)
Additional Skills:
- Quantitative problem-solving skills (this will be tested at the interview).
- Leadership experience, ideally including management of direct reports.
- Strong communication skills :
- Regular interaction with colleagues at varying levels of seniority.
- Adapting communication styles for audiences ranging from senior executives to junior colleagues impacted by new rules and processes.
- Self-starter who is proactive, results-driven, and flexible.
- Ability to work independently and deliver efficiently under tight timelines.
If this opportunity aligns with your expertise and aspirations, please send your CV to .
Application Deadline: Monday, 23 December 2024.
Quantitative Business Analyst | Financial Risk Models and Market Data employer: Barclay Simpson
Contact Detail:
Barclay Simpson Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Business Analyst | Financial Risk Models and Market Data
✨Tip Number 1
Familiarize yourself with the specific market risk metrics mentioned in the job description, such as VaR and HVaR. Being able to discuss these concepts confidently during your interview will demonstrate your expertise and understanding of the role.
✨Tip Number 2
Brush up on your Python programming skills, especially in relation to handling large datasets. Consider working on a small project or two that showcases your ability to manipulate and analyze market data using Python.
✨Tip Number 3
Prepare to discuss your experience with SQL and how you've used it to manage and analyze market data sets. Be ready to provide examples of how you've solved quantitative problems in previous roles.
✨Tip Number 4
Since strong communication skills are essential for this role, practice explaining complex financial concepts in simple terms. This will help you connect with interviewers at all levels and show that you can adapt your communication style effectively.
We think you need these skills to ace Quantitative Business Analyst | Financial Risk Models and Market Data
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Quantitative Business Analyst position. Familiarize yourself with terms like market risk, derivatives pricing, and financial markets regulations.
Tailor Your CV: Customize your CV to highlight relevant experience in project management, analysis, and visualization of large market data sets. Emphasize your Python programming skills and SQL experience, as these are crucial for the role.
Craft a Strong Cover Letter: Write a compelling cover letter that showcases your quantitative problem-solving skills and leadership experience. Mention specific examples of how you've handled large datasets and your understanding of market risk metrics.
Proofread Your Application: Before submitting, carefully proofread your application materials. Ensure there are no typos or grammatical errors, and that your communication style is professional yet approachable, reflecting the strong communication skills required for the role.
How to prepare for a job interview at Barclay Simpson
✨Showcase Your Statistical Skills
Be prepared to discuss your statistical and mathematical background in detail. Highlight specific projects where you analyzed large market data sets, and be ready to explain the methodologies you used.
✨Demonstrate Your Python Proficiency
Since Python programming is crucial for this role, come equipped with examples of how you've used Python to build solutions with large datasets. If possible, share any relevant code snippets or projects during the interview.
✨Understand Market Risk Metrics
Familiarize yourself with key market risk metrics such as VaR, HVaR, and IRC. Be ready to discuss how these metrics apply to different asset classes and how you've utilized them in past roles.
✨Communicate Effectively
Given the need for strong communication skills, practice adapting your communication style for different audiences. Prepare to explain complex concepts in a simple manner, especially when discussing financial regulations and policies.
