At a Glance
- Tasks: Lead the integration of advanced ML models into investment strategies.
- Company: Join a top-tier systematic hedge fund in London/NYC.
- Benefits: Enjoy a hybrid work model with flexible hours and competitive salary up to £1m.
- Other info: Candidates will receive feedback within 24 hours; reach out to james@durlstonpartners.com.
- Why this job: Be at the forefront of ML innovation in finance, impacting real-world trading strategies.
- Qualifications: PhD in a relevant field with proven ML experience in high-stakes environments required.
The predicted salary is between 72000 - 120000 £ per year.
Machine Learning Specialist - Elite Systematic shop - London/NYC - Up to £1m
One of our leading Systematic Hedge Fund clients is looking to introduce advanced ML models and techniques into their investment process and is looking for an experienced ML specialist to lead this endeavour.
The mandate is significant, with the successful individual being responsible for the application and adoption of ML across all of the firm's strategies and teams.
The firm is looking for someone with a solid publication record as well as practical experience using ML in applied settings.
Key Responsibilities:
- Serve as a subject matter expert in machine learning, advising teams across all asset classes.
- Identify and evaluate opportunities to apply ML techniques to optimize trading strategies, portfolio management, and infrastructure.
- Collaborate with quantitative researchers, data scientists, and engineers to design and implement end-to-end ML solutions.
- Develop, test, and deploy production-grade ML models, ensuring their robustness, scalability, and real-world applicability.
- Stay at the forefront of ML research and industry advancements, assessing their potential impact and relevance to systematic trading.
Qualifications:
- PhD in Computer Science, Mathematics, Statistics, or a related field, with a strong publication record.
- Proven experience applying ML techniques in real-world, high-stakes environments (finance, trading, or similarly complex domains preferred).
- Deep understanding of ML algorithms, statistical models, and optimization techniques.
- Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) and familiarity with distributed computing.
- Ability to think from first principles and drive projects independently, with an ownership mindset.
- Strong analytical, problem-solving, and critical-thinking skills.
- Experience with large-scale time series data or alternative data sources is a plus.
Salary: Up to £1m TC
WFH: Hybrid but flexible
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Information Technology and Research
Industries: Financial Services and Investment Management
For more information, please get in touch. Successful candidates will receive a response in 24 hours. james@durlstonpartners.com
#J-18808-LjbffrMachine Learning Specialist employer: DURLSTON PARTNERS
Join a leading conversational AI platform that is not only redefining customer experience but also fostering a high-trust work environment where your technical decisions matter. With a focus on innovation and excellence, this in-office role offers you the chance to collaborate with top-tier talent, engage in meaningful projects, and enjoy ample opportunities for professional growth in a fast-paced setting. Experience the unique advantage of working at the forefront of AI technology, contributing to solutions that impact millions.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Specialist
✨Tip Number 1
Network with professionals in the finance and machine learning sectors. Attend industry conferences, webinars, or meetups to connect with potential colleagues and mentors who can provide insights into the role and the company culture.
✨Tip Number 2
Showcase your practical experience by discussing specific projects where you've successfully implemented ML techniques. Be prepared to explain the challenges you faced and how you overcame them, as this demonstrates your problem-solving skills.
✨Tip Number 3
Stay updated on the latest advancements in machine learning and finance. Follow relevant research papers, blogs, and podcasts to ensure you can speak knowledgeably about current trends and how they might apply to the firm's strategies.
✨Tip Number 4
Prepare for technical discussions by brushing up on your Python skills and familiarising yourself with key ML libraries like TensorFlow and PyTorch. Being able to demonstrate your coding abilities during interviews can set you apart from other candidates.
We think you need these skills to ace Machine Learning Specialist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your relevant experience in machine learning, particularly in finance or trading. Emphasise your publication record and any practical applications of ML techniques you've led.
Craft a Strong Cover Letter:In your cover letter, explain why you're passionate about machine learning and how your skills align with the firm's goals. Mention specific projects where you've successfully implemented ML solutions.
Showcase Technical Skills:Clearly list your proficiency in Python and ML libraries like TensorFlow and PyTorch. If you have experience with distributed computing or large-scale time series data, make sure to highlight that as well.
Demonstrate Problem-Solving Abilities:Provide examples in your application that showcase your analytical and critical-thinking skills. Discuss how you've approached complex problems and the impact of your solutions in previous roles.
How to prepare for a job interview at DURLSTON PARTNERS
✨Showcase Your Expertise
Be prepared to discuss your previous work in machine learning, especially any publications or projects that demonstrate your expertise. Highlight specific ML techniques you've applied in real-world scenarios, particularly in finance or trading.
✨Understand the Firm's Strategies
Research the hedge fund's investment strategies and be ready to suggest how ML can enhance their processes. This shows your initiative and understanding of their business model, making you a more attractive candidate.
✨Demonstrate Collaboration Skills
Since the role involves working with various teams, be ready to share examples of how you've successfully collaborated with quantitative researchers, data scientists, or engineers in the past. Emphasise your ability to communicate complex ideas clearly.
✨Stay Current with ML Trends
Familiarise yourself with the latest advancements in machine learning and be prepared to discuss how these could impact systematic trading. Showing that you're proactive about staying updated will impress interviewers.
