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 opportunities to work on diverse projects and grow your career.
- 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 3+ years of machine learning experience.
The predicted salary is between 60000 - 80000 € per year.
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 employer: Graham Capital Management, L.P.
Graham Capital Management is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a Machine Learning Engineer to thrive. With a commitment to employee growth, the firm offers opportunities to work alongside world-class talent on cutting-edge projects that directly impact the investment strategies of global institutions. Located in London, Graham provides a dynamic work environment where diverse ideas are valued, and employees are encouraged to take ownership of their work while contributing to the firm's success.
Contact Detail:
Graham Capital Management, L.P. Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Graham Capital on LinkedIn or attend industry events. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio of your machine learning projects and be ready to discuss them in detail. We want to see how you tackle real-world problems and your thought process behind it.
✨Tip Number 3
Practice makes perfect! Brush up on your technical skills and be ready for coding challenges. We recommend using platforms like LeetCode or HackerRank to get comfortable with the types of questions you might face.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with machine learning, statistics, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team at Graham. Be genuine and let your personality come through – we love seeing that!
Showcase Your Projects:If you've worked on any interesting projects, especially those involving large datasets or machine learning, make sure to mention them. We’re keen to see how you’ve applied your skills in real-world scenarios, so don’t hold back!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at Graham!
How to prepare for a job interview at Graham Capital Management, L.P.
✨Know Your Stuff
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss your experience with large, unstructured data sets and how you've applied machine learning in real-world scenarios. This is your chance to showcase your technical skills!
✨Showcase Your Projects
Prepare to talk about specific projects you've worked on, especially those involving Python, Spark, or SQL. Highlight your role in these projects and the impact they had. This will demonstrate your hands-on experience and problem-solving abilities.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Think of examples where you've successfully communicated your findings to diverse audiences, as this will show your versatility.
✨Ask Insightful Questions
Prepare thoughtful questions about Graham's data science initiatives and how they integrate with other teams. This shows your genuine interest in the role and helps you understand how you can contribute to their innovative solutions.
