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For Companies At a Glance
- Tasks: Explore datasets, build GenAI solutions, and improve NLP/ML models for investment strategies.
- Company: Join Point72, a leading global alternative investment firm with a focus on innovation.
- Benefits: Enjoy private medical insurance, generous leave policies, wellness programmes, and tuition assistance.
- Why this job: Kickstart your career in finance and tech while making a real impact in investing.
- Qualifications: Degree in computer science or quantitative discipline; experience in NLP and Python required.
- Other info: Collaborative culture with excellent growth opportunities and commitment to diversity.
The predicted salary is between 36000 - 60000 £ per year.
Overview
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A Career with Point72’s Long/Short Equities Team. Long/short equity is Point72’s core strategy and its success is dependent upon our sector-based investing teams. Using fundamental research, our Research Analysts inform the investment strategies of our Portfolio Managers. Through our Point72 University, you have access to an unparalleled training and coaching curriculum – so you can create your best chance of success. We offer you a clear path based on your abilities, hard work, and performance. Join us for a career at the forefront of investing.
Responsibilities
- Explore and combine rich internal and external compliance approved textual datasets
- Formulate research hypothesis to derive alpha
- Build GenAI solutions, leveraging both internal models and permissible external APIs
- Turn unstructured text into usable data that can help provide inputs to the investment process and quantitative models
- Create systems to pull useful information from large collections of text
- Test and improve NLP and ML models so they are reliable and accurate
What’s Required
- Bachelor, Master’s or PhD degree in computer science or another quantitative discipline
- Experience in NLP, particularly LLMs
- Proficient in Python, SQL, and general software engineering principles (github, testing, etc.)
- Familiarity with data science stack
- Interest in financial markets
- Collaborative mindset
- Commitment to the highest ethical standards
We take care of our people
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
- Private Medical and Dental Insurances
- Generous parental and family leave policies
- Volunteer opportunities
- Support for employee-led affinity groups representing women, people of colour and the LGBTQ+ community
- Mental and physical wellness programmes
- Tuition assistance
- Non-contributory pension and more
About Point72
Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit https://point72.com/
Seniority level
- Entry level
Employment type
- Full-time
Job function
- Engineering and Information Technology
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L/S NLP/ML Engineer – London employer: Point72
Contact Detail:
Point72 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land L/S NLP/ML Engineer – London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Point72. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your NLP and ML projects. This is your chance to demonstrate what you can do beyond the CV – make it pop!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common coding challenges and be ready to discuss your thought process.
✨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 L/S NLP/ML Engineer – London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the L/S NLP/ML Engineer role. Highlight your experience with NLP, Python, and any relevant projects that showcase your skills. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background aligns with our needs. Don’t forget to mention your interest in financial markets – it’s a big plus for us!
Showcase Your Projects: If you've worked on any cool projects related to NLP or ML, make sure to include them in your application. We love seeing practical examples of your work, especially if they demonstrate your problem-solving skills and creativity.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Point72
✨Know Your NLP and ML Inside Out
Make sure you brush up on your knowledge of Natural Language Processing and Machine Learning, especially focusing on large language models. Be prepared to discuss specific projects you've worked on and how they relate to the role.
✨Show Off Your Coding Skills
Since proficiency in Python and SQL is a must, practice coding challenges beforehand. You might be asked to solve problems on the spot, so being comfortable with GitHub and testing principles will definitely give you an edge.
✨Understand the Financial Markets
Familiarise yourself with the basics of financial markets and how they operate. Being able to connect your technical skills to real-world investment strategies will impress your interviewers and show your genuine interest in the field.
✨Demonstrate Your Collaborative Spirit
Point72 values a collaborative mindset, so be ready to share examples of how you've worked effectively in teams. Highlight any experiences where you’ve contributed to group projects or helped others succeed.
