At a Glance
- Tasks: Join our Data Science team to develop innovative machine learning solutions for financial strategies.
- Company: Graham Capital Management, a leading alternative investment manager with a focus on innovation.
- Benefits: Competitive salary, collaborative culture, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on collaboration and career development.
- Why this job: Work with cutting-edge technology and talented professionals to make a real impact in finance.
- Qualifications: Degree in a quantitative field and experience with machine learning on large data sets.
The predicted salary is between 60000 - 80000 £ per year.
Graham Capital Management, L.P. (collectively with its affiliates, "Graham") is an alternative investment manager founded in 1994 by Kenneth G. Tropin. Specializing in discretionary and quantitative macro strategies, Graham is dedicated to delivering strong, uncorrelated returns across a wide range of market environments. As one of the industry’s longest-standing global macro and trend-following managers, Graham remains committed to innovation, evolving its strategies through a robust investment, technology, and operational infrastructure.
Graham harnesses the synergies between its discretionary and quantitative trading businesses to offer a broad suite of complementary alpha strategies, each built on the principles of thoughtful portfolio construction, active risk management, and diversification by design. Graham invests significant proprietary capital alongside its clients – including global institutions, endowments, foundations, family offices, sovereign wealth funds, investment management advisors, and qualified individual investors – reinforcing alignment of interests across all strategies. The foundation of Graham’s sustainability and success is the experience and contributions of its people. The firm seeks to cultivate talent, encourage the diversity of ideas, and respect the contributions of all. In turn, each employee shares in the responsibility of strengthening those around them.
Description: Graham Capital Management, L.P. is seeking a ML Engineer to join our Data Science team, a future-looking technical arm of Graham Capital. We envision, design, prototype and implement the processes that feed Quantitative Research and Discretionary Trading teams as well as the broader firm. We are passionate about what we do and welcome every opportunity to prove it. The Data Science department straddles traditional Data Science and Engineering roles as well as the application of Machine Learning & AI. We work closely with Quant Researchers, Portfolio Managers, Operations and Execution to continuously improve upon our offering.
Every day we work to transform our business through data, technology, and the insights we provide our stakeholders. At Graham Capital, our systems feed live models around the clock, span billions of market data ticks, an ever-increasing corpus of news and other texts as well as a broad spectrum of financial and alternative data. Our objective is to support the research process by providing our stakeholders with all the right pieces to succeed in their jobs.
Responsibilities: You will be part of a growing team within Data Science. You will work alongside world-class talent to find innovative solutions to some of the most interesting problems on the buy-side. You will work closely with other areas such as Technology, Quantitative Research and Portfolio Manager groups as well as Risk and Operations to learn about problems they face with respect to data and ultimately develop cutting edge solutions. Your focus will be to dive deep into multiple data sets to understand relationships, develop time series, forecasting models, and support quant strategies, and provide new insights and leverage state-of-the-art machine learning and advanced statistical methods to produce the best data sources for the fund.
Requirements:
- Undergraduate or higher degree in Computer Science, Engineering, Operations Research, or other quantitative discipline
- 3+ years of hands-on experience with Machine Learning and Statistics on large, unstructured, data sets
- Experience writing production code for multi-client systems serving model results is a great plus
- Ability to clearly communicate research findings to technical and nontechnical stakeholders
- Full-stack experience with Python (preferred) or C++, Spark/Scala, SQL or other distributed data processing technologies as well as experience working comfortably building and deploying services and models in containerized environments
- Experience with scientific computing, statistics, optimization, time series, panel data, etc.
- Comfortable handling multiple projects to solve varied problems working with multiple teams
- Detail-oriented mindset
- Sense of ownership of his/her work, working well both independently as well as collaboratively
This role requires commuting into our London office Mondays through Fridays.
Machine Learning Engineer in London employer: Graham Capital Management
Graham Capital Management, L.P. is an exceptional employer that fosters a culture of innovation and collaboration within its Data Science team. Located in the heart of London, employees benefit from a dynamic work environment that encourages professional growth through exposure to cutting-edge machine learning applications and close collaboration with industry experts. With a strong commitment to diversity and employee development, Graham offers a unique opportunity for individuals to contribute meaningfully while advancing their careers in a supportive and forward-thinking organisation.
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We think this is how you could land Machine Learning Engineer in London
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We think you need these skills to ace Machine Learning Engineer 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!
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Craft a Tailored Cover Letter:For a full-time role at Graham Capital Management, 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.
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How to prepare for a job interview at Graham Capital Management
✨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
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 Graham Capital Management!
✨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.
