At a Glance
- Tasks: Develop trading strategies and analyse data to drive alpha generation in commodities.
- Company: Join DRW, a leading trading firm with a culture of innovation and respect.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative team atmosphere with a focus on integrity and high expectations.
- Why this job: Make an impact in global markets using cutting-edge technology and data analysis.
- Qualifications: Degree in a quantitative field and experience with AI and large datasets.
The predicted salary is between 36000 - 60000 £ per year.
DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it’s how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.
DRW are looking for an experienced Quant Researcher to join our global commodities trading team to aid in alpha generation, research, development, and maintenance of analytics infrastructure.
Responsibilities:
- Developing systematic trading strategies and alpha generating signals across commodity markets
- Enhancing data collection procedures to support improved design, development and maintenance of data pipelines to be used in research/trading
- Analyze large, diverse datasets to identify trends as well as building and maintaining models to support trading decisions, including the use of AI and LLMs
- Extract and organize data from a number of source options, performing quantitative analysis in support of trading
- Assist in the development of analytical tools
- Translate business needs into data science projects
- Collaborate with stakeholders at each stage of project
- Communicate projects and results to audiences with different backgrounds
- Create and maintain post-trade diagnostics tools across various strategies
Qualifications:
- A bachelor’s, master’s, or PhD in mathematics, statistics, physics, engineering, computer science or related field
- Experience using AI and LLMs
- Passion and interest for a quant researcher role solving real-world business problems
- Minimum of two years' experience in alpha generating role
- Experience working with large datasets, data cleaning, preprocessing, and feature engineering
- Experience building, validating, deploying, monitoring, and updating predictive models
- Excellent programming and scripting skills
- Experience working independently and delivering results
- Excellent written and oral communication skills, experience communicating complex ideas clearly and concisely to peers and stakeholders
- Strong collaborative intent, strong outcome driven focus
- Positive, team focused attitude
Quantitative Researcher - Commodities in London employer: DRW
DRW is an exceptional employer that fosters a culture of innovation and integrity, making it an ideal place for professionals seeking meaningful work in the dynamic field of trading. Located in London, the Office Space Planner role offers opportunities for collaboration with talented teams, involvement in impactful projects, and the potential for career growth within a supportive environment. With a commitment to employee autonomy and respect, DRW empowers its staff to thrive while contributing to the company's success.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher - Commodities in London
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We think you need these skills to ace Quantitative Researcher - Commodities in London
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 DRW, 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 DRW. 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 DRW
✨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!
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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
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✨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.
