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- Tasks: Collaborate with traders and analysts to generate market insights and actionable trade ideas.
- Company: Dynamic investment firm focused on commodities and quantitative research.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Fast-paced environment with a focus on innovation and teamwork.
- Why this job: Dive into the exciting world of commodities and make a real impact on investment strategies.
- Qualifications: PhD, MSc, or BSc in a quantitative field; strong C++ and Python skills required.
The predicted salary is between 70000 - 90000 £ per year.
Directly work with portfolio managers, traders, and fundamental analysts to generate differentiated market insights and actionable trade ideas.
Key Responsibilities:
- Contribute to the research architecture and analytics platform used by the investment team.
Qualifications & Requirements:
Education: PhD, MSc, or BSc in a highly quantitative discipline such as mathematics, physics, computer science, engineering, statistics, economics, or operations research.
Technical Skills:
- Strong C++ skills, with experience building high-performance analytical libraries and models.
- Strong Python skills for research, prototyping, data analysis, and workflow orchestration.
- Experience designing and integrating models into front office risk platforms and pricing tools.
Experience: At least 5 years of experience in a quantitative research, commodities, logistics, or applied modeling environment.
Quantitative / Research Skills:
- Strong grounding in probability, statistics, linear algebra, optimization, and numerical methods.
- Experience with Quantitative Approaches: Time series analysis, forecasting, simulation, optimization under constraints, network and flow models, stochastic modeling.
- Ability to formulate ambiguous market questions into testable hypotheses and practical research outputs.
Market / Domain Knowledge:
- Experience in, or strong interest in learning about, physical commodity markets with emphasis on energy markets.
- Familiarity with inventory and storage economics, freight markets, transport constraints, pipeline, terminal, warehouse, vessel, rail and truck logistics, regional dislocations and infrastructure bottlenecks, physical optionality embedded in commodity systems.
- Exposure to oil, gas, power, refined products, metals, or agricultural commodities is a plus.
Preferred Experience:
- Prior experience in front-office quantitative, trading, or investment-oriented roles.
- Experience building models used directly in risk platforms, trade evaluation, or idea generation.
- Familiarity with SQL/NoSQL databases, distributed data workflows, or DAG-based systems.
- Knowledge of machine learning techniques where relevant to forecasting or classification.
Personal Attributes:
- Strong commercial instincts and interest in applying quantitative research to investment decisions.
- Ability to work independently and as part of a team.
- Intellectually curious, highly analytical, and motivated by complex market problems.
- Comfortable working directly with investors and operating in a fast-paced front-office environment.
Quant Researcher, Commodities in London employer: Balyasny Asset Management LP
Contact Detail:
Balyasny Asset Management LP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Researcher, Commodities in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend conferences, webinars, or local meetups related to commodities and quantitative research. You never know who might have a lead on your dream job!
✨Show Off Your Skills
Create a portfolio showcasing your projects and models. Whether it's a GitHub repository or a personal website, let your work speak for itself. This is especially important for roles that require strong C++ and Python skills!
✨Ace the Informational Interview
Reach out to professionals in the field for informational interviews. Prepare thoughtful questions about their experiences and insights into the market. This not only builds your network but also gives you valuable information to tailor your approach.
✨Apply Through Our Website
Don’t forget to check out our job listings on the StudySmarter website! Applying directly through us can give you an edge, as we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Quant Researcher, Commodities in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your strong C++ and Python skills in your application. We want to see how you've used these languages to build analytical libraries or models, so don’t hold back on the details!
Quantitative Experience Matters: Since we’re looking for someone with at least 5 years of experience, be sure to showcase your background in quantitative research or commodities. Share specific examples of how you've tackled complex market problems.
Connect the Dots: When discussing your experience, try to connect it to the responsibilities outlined in the job description. Show us how your past work aligns with generating actionable trade ideas and insights for portfolio managers and traders.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and get to know you better, so don’t miss out!
How to prepare for a job interview at Balyasny Asset Management LP
✨Know Your Numbers
Brush up on your quantitative skills, especially in probability, statistics, and linear algebra. Be ready to discuss how you've applied these concepts in real-world scenarios, particularly in commodities or financial markets.
✨Showcase Your Coding Skills
Since strong C++ and Python skills are crucial, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice writing clean, efficient code and be ready to explain your thought process.
✨Understand the Market Landscape
Familiarise yourself with current trends in physical commodity markets, especially energy. Be prepared to discuss recent developments and how they could impact trading strategies. This shows your genuine interest and market knowledge.
✨Prepare for Hypothetical Scenarios
Expect to tackle ambiguous market questions during the interview. Practice formulating these into testable hypotheses and think about how you would approach research and analysis. This will demonstrate your analytical thinking and problem-solving skills.