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- Tasks: Support portfolio managers by building alpha research tools and analysing large datasets.
- Company: Balyasny Asset Management, a leading institutional investment firm with a vibrant culture.
- Benefits: Competitive salary, professional growth opportunities, and a dynamic work environment.
- Why this job: Join a team that empowers you to innovate and make impactful decisions in finance.
- Qualifications: Advanced degree in a quantitative field and strong Python programming skills required.
- Other info: Ideal for self-motivated individuals eager to collaborate and excel in a trading environment.
The predicted salary is between 50000 - 70000 £ per year.
Balyasny Asset Management L.P. (BAM) founded in 2001, is an institutional investment firm dedicated to delivering consistent, uncorrelated absolute returns in all market environments. BAM has offices in Chicago, New York, Greenwich, San Francisco, Hong Kong and London. At BAM, we are our talent. We are a growing firm that offers a multitude of professional opportunities. Through BAM's selective hiring process, we target the best and brightest in the business, and strive to create an environment which attracts and retains top talent. Maintaining a culture where people are energized to come to work is paramount to our success. Our team is motivated to perform each and every day. As a result, BAM has built a reputation as a firm that provides the tools necessary for talented individuals to achieve their goals and reach their highest potential.
KEY RESPONSIBILITIES
- Support portfolio manager and analysts in building out bespoke alpha research tools using in-house analytics.
- Analyze large datasets related to credit and municipal bonds to identify inefficiencies, opportunities, and risks.
- Work closely with the investment team and build valuation tools and screeners to improve the trading and filtration process.
- Test various trading strategies, perform ad-hoc research, and deliver the results via Excel/Python framework.
- Support trading and risk management with scenario analysis, relative value, and basis trading analytics.
- Perform tasks with minimum supervision and exercise sound judgment.
REQUIRED QUALIFICATIONS
- Advanced degree (MS/PhD preferred) in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, or Finance.
- 2+ years of experience in a quantitative or research role (preferably in fixed income/credit/munis).
- Strong programming skills in Python.
- Deep understanding of credit products and municipal bonds; familiarity with market data sources (TRACE, EMMA, Bloomberg, etc.).
- Experience with statistical/ML modeling and backtesting frameworks.
- Self-motivated, detail-oriented, and able to communicate complex ideas clearly to technical and non-technical audiences.
THE IDEAL CANDIDATE
- Experience working with traders or in a trading environment.
- Familiarity with risk management, portfolio construction, or pricing in fixed income.
- Strong desire to work collaboratively with the team.
DOCUMENTATION & ORGANIZATION SKILLS
- Documentation skills – ability to represent ideas, requirements, and problems in clear and concise documents.
- Outstanding attention to detail and strong organization skills.
Quantitative Researcher - Multi-Asset Arbitrage in City of Westminster employer: Balyasny Asset Management LP
Contact Detail:
Balyasny Asset Management LP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher - Multi-Asset Arbitrage in City of Westminster
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at BAM or similar firms. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio of projects or research, make sure to highlight them in conversations. Demonstrating your expertise in Python and quantitative analysis can really set you apart.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss how you've tackled complex datasets or trading strategies in the past—real examples go a long way!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of our team at BAM.
We think you need these skills to ace Quantitative Researcher - Multi-Asset Arbitrage in City of Westminster
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Quantitative Researcher. Highlight your relevant experience in quantitative fields and any specific projects that showcase your skills in Python and data analysis.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background aligns with BAM's mission. Be sure to mention any experience you have with credit products or trading environments.
Showcase Your Skills: Don’t forget to highlight your programming skills and any statistical modelling experience. If you've worked on relevant projects, include them! This is your opportunity to demonstrate your technical prowess.
Apply Through Our Website: We encourage you to apply 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!
How to prepare for a job interview at Balyasny Asset Management LP
✨Know Your Numbers
As a Quantitative Researcher, you'll be expected to handle large datasets and complex analyses. Brush up on your statistics and programming skills, especially in Python. Be ready to discuss specific projects where you've used these skills to derive insights or solve problems.
✨Understand the Market
Familiarise yourself with credit products and municipal bonds, as well as market data sources like TRACE and Bloomberg. During the interview, demonstrate your knowledge of current market trends and how they might impact investment strategies. This shows you're not just a number cruncher but also understand the bigger picture.
✨Showcase Your Collaboration Skills
BAM values teamwork, so be prepared to share examples of how you've worked effectively with others in a trading or research environment. Highlight any experiences where you supported portfolio managers or analysts, and how your contributions led to successful outcomes.
✨Communicate Clearly
You’ll need to explain complex ideas to both technical and non-technical audiences. Practice articulating your thought process and findings from past projects in a clear and concise manner. This will help you stand out as someone who can bridge the gap between data and decision-making.