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- Tasks: Design and develop models for alpha generation in a fast-paced trading environment.
- Company: Join a leading firm in liquidity strategies, optimising trading and execution approaches.
- Benefits: Enjoy a competitive salary, performance bonuses, and comprehensive benefits.
- Why this job: Be part of a collaborative team driving innovation in quantitative finance with real market impact.
- Qualifications: 5+ years in Quantitative Finance, PhD or Master's in Statistics, and proficiency in Python/KDB required.
- Other info: This role offers a unique opportunity to work on complex financial models in a dynamic setting.
The predicted salary is between 96000 - 160000 £ per year.
The Central Liquidity Strategies (CLS) business manages a number of portfolios and products designed to optimize the firm’s trading and execution approach by providing internal liquidity solutions for portfolio managers on both a risk and agency basis. We are seeking an Alpha Researcher with experience in return/toxicity forecasting as it relates to market-making business offering pricing on larger blocks of equities either via outright risk pricing or other product structures.
Principal Responsibilities
- Modelling: Design and develop models to assist in alpha generation. Areas include automated evaluation of signal performance over time and feature engineering techniques to drive improvements. Combination of multiple signals to produce a single usable alpha for different contexts and attribution of performance. Robust estimation of key metrics such as signal correlations, decay, turnover and risk.
- Rigorous Grounding: Given inherent complexity and high dimensionality, employ methods to avoid overfitting and poor OOS performance based on sound statistical reasoning.
- Collaboration: Work with team members to decide the overall direction, design, and architecture of the platform, and collaborate with key stakeholders across the business.
Qualifications/Skills Required
- Required Experience: 5+ years of experience in Quantitative Finance setting, with a proven track record of developing robust alpha models, preferably in an Equities context.
- Education: PhD or Master’s degree in Statistics, or a related field with an excellent understanding of the theory behind statistical and machine learning methods.
- Technical Skills: Proficiency in Python and/or KDB, preferably both.
The estimated base salary range for this position is $160,000 to $250,000, which is specific to New York and may change in the future. Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. When finalizing an offer, we take into consideration an individual’s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.
Quantitative Researcher - Execution Services employer: Millennium Management LLC
Contact Detail:
Millennium Management LLC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher - Execution Services
✨Tip Number 1
Familiarise yourself with the latest trends in quantitative finance, especially in alpha generation and market-making. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of quantitative research. Attend industry conferences or webinars where you can meet potential colleagues and learn about their experiences. This could give you insights into what the company values in a candidate.
✨Tip Number 3
Brush up on your Python and KDB skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source projects that involve these technologies to demonstrate your proficiency.
✨Tip Number 4
Prepare to discuss your previous experience in developing alpha models. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will showcase your problem-solving skills and technical expertise.
We think you need these skills to ace Quantitative Researcher - Execution Services
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in quantitative finance, particularly in developing alpha models. Emphasise your technical skills in Python and KDB, as well as any relevant projects or research that demonstrate your expertise.
Craft a Strong Cover Letter: In your cover letter, explain why you are interested in the Quantitative Researcher position and how your background aligns with the responsibilities outlined in the job description. Mention specific experiences that showcase your ability to model and collaborate effectively.
Showcase Relevant Projects: If you have worked on projects related to return or toxicity forecasting, be sure to include these in your application. Describe the methodologies you used and the outcomes achieved, as this will demonstrate your practical experience in the field.
Highlight Collaboration Skills: Since collaboration is key for this role, mention any experiences where you worked with teams or stakeholders to achieve a common goal. This could include cross-functional projects or instances where you contributed to the design and architecture of a platform.
How to prepare for a job interview at Millennium Management LLC
✨Showcase Your Modelling Skills
Be prepared to discuss your experience in designing and developing models for alpha generation. Highlight specific projects where you automated signal performance evaluation or combined multiple signals to create usable alpha.
✨Demonstrate Statistical Knowledge
Since the role requires a strong grounding in statistical methods, be ready to explain how you've avoided overfitting in your previous work. Discuss any techniques you've used to ensure robust out-of-sample performance.
✨Collaboration is Key
This position involves working closely with team members and stakeholders. Prepare examples of how you've successfully collaborated on projects in the past, focusing on your ability to contribute to the overall direction and design of a platform.
✨Technical Proficiency Matters
Make sure to highlight your proficiency in Python and/or KDB during the interview. Be ready to discuss specific instances where you've applied these skills in a quantitative finance setting, particularly in equities.
