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- Tasks: Develop innovative alpha signals and enhance portfolio construction methodologies for global equity markets.
- Company: Dynamic asset management firm focused on quantitative research and collaboration.
- Benefits: Competitive salary, diverse work environment, and opportunities for continuous learning.
- Other info: Embrace diversity and inclusion in a supportive workplace.
- Why this job: Join a cutting-edge team and make a real impact in the finance world.
- Qualifications: PhD in machine learning or related field; experience in quantitative research preferred.
The predicted salary is between 50000 - 70000 £ per year.
As a Senior Associate in the quantitative research team, you will contribute to the research and development of alpha signals, portfolio construction methodologies, and risk models for global equity markets. The ideal candidate will have a PhD in machine learning, with a strong preference for expertise in reinforcement learning, and 0-3 years of relevant experience. You will collaborate closely with portfolio managers, technologists, and other researchers to translate research insights into actionable investment strategies.
Job Responsibilities
- Alpha Signal Development: Research and develop novel alpha signals using traditional and alternative data sources, enhancing the return forecasting models for stocks.
- Model Enhancement: Improve return forecasting models and portfolio construction frameworks for global equity markets with a focus on applying reinforcement learning and other advanced machine learning techniques.
- Data Analysis: Apply statistical, econometric, and machine learning methods to large, complex datasets to extract actionable insights.
- Research Integration: Work with technology teams to integrate research models into production systems and ensure robust implementation.
- Collaboration: Partner with portfolio managers and other stakeholders to translate quantitative research into investment decisions.
- Continuous Learning: Stay current with academic and industry developments in quantitative finance, machine learning, and data science.
Required Skills, Qualifications and Capabilities
- Education: PhD in machine learning, computer science, statistics or a related quantitative discipline. Specialization in reinforcement learning is highly desirable.
- Experience: Experience in quantitative research, data science, or a related field (industry or academic).
- Technical Skills: Strong programming skills in Python; experience with machine learning libraries.
- Quantitative Modeling: Familiarity with quantitative modeling, portfolio construction, and equity markets.
- Data Handling: Experience working with large, complex, and alternative datasets.
- Communication: Excellent verbal and written communication skills, with the ability to present complex ideas to both technical and non-technical audiences.
- Collaboration: Demonstrated ability to work effectively in a team environment.
- Initiative: Strong problem-solving skills and intellectual curiosity; ability to drive research projects independently.
We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Asset Management, Equity Quant Researcher, Associate in London employer: Jpmorgan Chase & Co.
Contact Detail:
Jpmorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Asset Management, Equity Quant Researcher, Associate in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the asset management and quantitative research fields. Use platforms like LinkedIn to connect with people who work at companies you're interested in, and don't be shy about asking for informational interviews.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and data analysis. This is your chance to demonstrate your expertise in reinforcement learning and how you can apply it to real-world problems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past experiences and how they relate to the role of an Equity Quant Researcher. Practice explaining complex concepts in simple terms!
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Make sure to tailor your application to highlight your relevant experience and skills, and don’t forget to follow up after submitting your application to show your enthusiasm.
We think you need these skills to ace Asset Management, Equity Quant Researcher, Associate in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience in quantitative research and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or research!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about equity quant research and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills: Since we’re looking for strong programming skills, make sure to mention your experience with Python and any machine learning libraries you’ve used. If you’ve worked on specific projects, give us the details – we want to know what you can bring to the table!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your Algorithms
Brush up on your knowledge of machine learning algorithms, especially reinforcement learning. Be ready to discuss how you’ve applied these techniques in your previous work or research. This will show that you’re not just familiar with the theory but can also translate it into practical applications.
✨Showcase Your Data Skills
Prepare to talk about your experience with large datasets and the tools you've used for data analysis. Highlight specific projects where you extracted actionable insights from complex data. This will demonstrate your ability to handle the kind of data they work with.
✨Collaboration is Key
Since the role involves working closely with portfolio managers and technologists, be ready to share examples of how you’ve successfully collaborated in a team setting. Discuss any cross-functional projects you've been part of and how you communicated complex ideas to non-technical stakeholders.
✨Stay Current and Curious
Show your passion for continuous learning by discussing recent developments in quantitative finance or machine learning that excite you. This could be a recent paper you read or a new technique you want to explore. It reflects your intellectual curiosity and commitment to staying at the forefront of the field.