Quantitative Developer - Trading Algorithms (Basé à London)

Jobleads
Greater London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Quantitative Developer | Systematic Research

Quantitative Developer - C#

Quantitative Developer

Quantitative Developer

Quantitative Developer (python/react)

Quantitative Developer

Quantitative Developer - Trading Algorithms

Job Function Summary
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 a highly driven, results-oriented Senior Quantitative Developer with a strong background in building trading algorithms and a deep understanding of market microstructure and execution strategies to build a greenfield internal algorithmic trading platform. This role requires a combination of technical expertise, industry knowledge, and leadership skills to develop and optimize trading algorithms tailored to the businesses’ trading objectives.

Principal Responsibilities

  1. Algorithm Development:Developing custom trading algorithms with tailored execution outcomes that implement our portfolio optimization approach. Developing a framework that relies on internal signals and facilitates its use by a broader set of teams with their own signals, either independently or collaboratively.
  2. Simulation:Develop a framework of simulators that use market data and trade history (or models) to evaluate the efficacy of algorithmic logic changes.
  3. Collaboration with Quant Analysts:Partner with quantitative research analysts to productionize market microstructure and short-term signal models.
  4. Performance Evaluation:Develop execution analysis reporting with appropriate benchmarks to evaluate the performance of custom algorithms.
  5. Monitoring Tools:Develop intraday and post-trade monitoring tools to monitor and troubleshoot algorithm performance.

Qualifications/Skills Required

  1. Experience:10+ years of relevant experience in the trading and finance industry.
  2. Market Microstructure Expertise:Domain expert in the market microstructure of cash equities. Knowledge of liquid futures market structure is a bonus.
  3. Development Skills:Significant hands-on development experience in event-driven, real-time trading processes. Proficiency in C++ is preferred. If using Java, must demonstrate techniques that maximize runtime performance; proficiency with techniques that cover best-in-class software-based latency; experience with FPGA is a plus but not required.
  4. Trade & Market Data:Reasonable amount of experience with understanding and coding trade and market data.
  5. Leadership:Experience as a hands-on development lead, mentoring and guiding junior developers.
  6. Education:Bachelor's or Master's degree in CS, Electrical & Electronic Eng, Biochem, applied math or statistics.
  7. Technical Skills:Strong programming skills in C++ or Java, with a focus on event-driven real-time trading processes.
  8. Analytical Skills:Excellent quantitative and analytical skills, with the ability to interpret complex data and develop actionable insights.
  9. Communication:Strong verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders.
  10. Problem-Solving:Proven ability to solve complex problems and think critically in high-pressure situations.
  11. Team Player:Ability to work effectively in a team-oriented environment, collaborating with cross-functional teams.

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.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Jobs

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.