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- Tasks: Join a dynamic team to develop AI-driven trading signals using machine learning.
- Company: Point72 is a leading investment firm focused on innovative research and technology.
- Benefits: Enjoy competitive salary, comprehensive benefits, and opportunities for professional growth.
- Why this job: Be part of a collaborative environment that values creativity and cutting-edge technology.
- Qualifications: Master’s or PhD in machine learning or related fields; strong analytical skills required.
- Other info: No prior financial industry experience needed; remote work options available.
The predicted salary is between 90000 - 150000 £ per year.
Job Responsibilities
A highly collaborative, fast-growing team at Internal Alpha Capture (IAC), Point72 is developing AI-driven equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, proprietary data sources, and unparalleled computing power.
We are looking for exceptional machine learning researchers to join our efforts. Researchers will work closely with our experienced team members and apply the full breadth of their machine learning knowledge to unique, proprietary datasets, and develop novel trading signals that have high impact. Prior experience in the financial industry is not required.
Key responsibilities may include:
Desirable Candidates
The annual base salary range for this role is $150,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
Quantitative Researcher – Machine Learning employer: Point72
Contact Detail:
Point72 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher – Machine Learning
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning and AI, especially in areas like reinforcement learning and graph neural networks. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with the machine learning community by attending relevant meetups, webinars, or conferences. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals for the position.
✨Tip Number 3
Showcase your practical experience with machine learning libraries like Torch, JAX, or TensorFlow through personal projects or contributions to open-source initiatives. This hands-on experience can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your approach to problem-solving and research methodologies in detail. Be ready to explain how you would manage the research process and adapt existing models to new datasets, as this is a key aspect of the role.
We think you need these skills to ace Quantitative Researcher – Machine Learning
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and quantitative research. Emphasise any projects or roles where you've applied advanced machine learning techniques, especially those related to financial data.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for machine learning and your understanding of its application in finance. Mention specific skills or experiences that align with the job responsibilities outlined by Point72.
Showcase Your Technical Skills: In your application, clearly list your proficiency in machine learning libraries like Torch, JAX, or TensorFlow. Provide examples of how you've used these tools in past projects, particularly in handling large datasets.
Highlight Collaboration Experience: Since the role requires a collaborative approach, include examples of how you've worked effectively in teams. Discuss any experiences where you engaged with team members to achieve common goals in research or projects.
How to prepare for a job interview at Point72
✨Showcase Your Machine Learning Knowledge
Be prepared to discuss your understanding of various machine learning models, especially modern sequence models and reinforcement learning. Highlight any relevant projects or research you've conducted, and be ready to explain your thought process and methodologies.
✨Demonstrate Analytical Skills
Expect questions that assess your analytical and quantitative skills. Prepare to solve problems on the spot or discuss how you would approach a specific dataset. Use examples from your past experiences to illustrate your analytical mindset.
✨Emphasise Collaboration
Point72 values a collaborative environment, so be sure to express your willingness to work with others. Share examples of how you've successfully collaborated in previous roles, and discuss how you can contribute to a team-oriented research atmosphere.
✨Stay Updated on Industry Trends
Research the latest advancements in AI and machine learning before your interview. Be ready to discuss recent innovations and how they could apply to the role. This shows your commitment to staying informed and your proactive approach to identifying new opportunities.
