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For Companies At a Glance
- Tasks: Design and develop models for alpha generation in a dynamic trading environment.
- Company: Join Millennium, a leading investment management firm known for innovation and excellence.
- Benefits: Enjoy a competitive salary, performance bonuses, and comprehensive benefits.
- Why this job: Be part of a collaborative team driving impactful financial strategies in a fast-paced industry.
- Qualifications: 5+ years in Quantitative Finance with a PhD or Master's in Statistics required.
- Other info: This is a full-time, mid-senior level position based in London.
The predicted salary is between 120000 - 200000 £ 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.
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Finance and Sales
Industries: Investment Management
Quantitative Researcher - Execution Services employer: Millennium
Contact Detail:
Millennium 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 or mentors who can provide insights into the company culture and expectations.
✨Tip Number 3
Brush up on your technical skills, particularly in Python and KDB. Consider working on personal projects or contributing to open-source projects that showcase your ability to develop robust models and handle complex data.
✨Tip Number 4
Prepare to discuss your previous experiences in detail, focusing on specific projects where you developed alpha models. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will demonstrate your problem-solving abilities.
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 relevant experience in quantitative finance, particularly in developing alpha models. Emphasise your proficiency in Python and KDB, as well as any specific projects that demonstrate your skills in return/toxicity forecasting.
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 your experience with statistical methods and collaboration in team settings.
Showcase Your Technical Skills: Include specific examples of your technical skills in your application. Discuss any relevant projects or research where you applied statistical and machine learning methods, and how these contributed to alpha generation.
Highlight Collaboration Experience: Since collaboration is key for this role, provide examples of how you've worked with team members or stakeholders in previous positions. This could include joint projects, decision-making processes, or contributions to platform design.
How to prepare for a job interview at Millennium
✨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
Emphasise your ability to work collaboratively with team members and stakeholders. Share examples of how you've contributed to the overall direction and design of a project, showcasing your teamwork skills.
✨Technical Proficiency Matters
Make sure to highlight your proficiency in Python and KDB. Be prepared to discuss specific instances where you've used these tools to solve complex problems in quantitative finance.
