C# Developer - Top Systematic Hedge Fund - Up to £300K

Mondrian Alpha
London
1 month ago
Applications closed

Related Jobs

View all jobs

C# Developer

C++ Developer - Investment Tools and Signals

Net, C# Developer

Application Support Engineer, C# Developer,Azure,SRE

C++ Quant Developer - Systematic Equities - Top Buy Side Fund

C# Software Developer X 3

My client, a prestigious global hedge fund, is seeking a talented C# Software Developer to join their Quantitative Technology team in London.


In this role, you will work closely with quantitative researchers, portfolio managers, and other technology teams to build and enhance the tools, APIs, libraries, and user interfaces that underpin their quantitative trading strategies. Key projects will include designing and maintaining scalable data platforms, optimizing trading systems, and improving research workflows.


As part of a highly collaborative and innovative team, you will have direct exposure to senior technologists and researchers and will play a critical role in improving the firm’s ability to predict and trade movements in global financial markets.


This is an exceptional opportunity for a skilled developer with a passion for technology and quantitative finance to contribute to the core platforms that drive the research and trading of cutting-edge investment strategies.


Responsibilities:

  • Develop and maintain a world-class platform for large-scale data storage, transformation, and testing, leveraging modern open-source software, cloud, and distributed computing technologies.
  • Collaborate with researchers and technologists to design and implement solutions that meet business-critical needs.
  • Write and maintain high-quality, well-tested code across backend services, data storage, and UI layers.
  • Actively contribute to code reviews, knowledge-sharing, and technical design discussions.
  • Evaluate and adopt new technologies to ensure efficient and innovative delivery of business requirements.


Requirements:

  • 5+ years of professional software development experience, with strong skills in C#, Python, or C++.
  • Solid computer science fundamentals, including experience with distributed systems and large-scale data processing.
  • Collaborative nature, with the ability to work closely with portfolio managers, quantitative researchers, and other teams.
  • A strong interest in modern technology stacks and a pragmatic approach to adopting new tools and frameworks.
  • Problem-solving skills that span multiple technologies and business domains.


My client anticipates to pay a strong performer upwards of £300k year 1 total compensation package. As well as a market-leading compensation package, they offer exceptional benefits including a top-tier healthcare package, fully subsidised qualifications plus breakfast and lunch paid for each day.


To apply, either respond to this advert or send your CV directly to .

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.

Job-Hunting During Economic Uncertainty: Data Science Edition

Data science has become essential for modern businesses, enabling data-driven decisions that enhance efficiency, profitability, and strategic foresight. From predictive analytics in finance to recommendation engines in retail, data scientists sit at the crossroads of statistics, programming, and domain expertise, building models that translate raw information into tangible insights. Yet, when broader economic forces create uncertainty—through market downturns, shifting investor priorities, or internal budget constraints—data science roles can experience increased scrutiny, competition, and extended hiring cycles. Despite these pressures, data-driven approaches remain crucial to organizations looking to weather challenges and find opportunities in volatile environments. Whether you’re refining advanced machine learning techniques, fine-tuning data pipelines, or collaborating with business stakeholders on dashboards, your skill set is often still in demand. The key is adapting your job search strategy and personal branding to cut through the noise when fewer roles may be available. This article explores: Why economic headwinds affect data science hiring. Actionable strategies to stand out in a tighter job market. Ways to emphasize your technical and soft skills effectively. Techniques to maintain focus and resilience despite potential setbacks. How www.datascience-jobs.co.uk can help you secure the ideal data science position. By combining strategic thinking, polished communications, and adaptability, you can land a fulfilling data science role that leverages your expertise—even if the market feels more demanding.

How to Achieve Work-Life Balance in Data Science Jobs: Realistic Strategies and Mental Health Tips

Data science has quickly emerged as one of the most influential fields in the modern workplace, shaping how businesses make critical decisions and expanding our understanding of everything from consumer behaviour to public health trends. As the global demand for data insights continues to rise, companies of all sizes are seeking professionals who can effectively harness analytics and machine learning to drive innovation. Yet, this promise of limitless opportunity comes with significant challenges. Data scientists often grapple with large volumes of complex data, tight project deadlines, cross-functional collaboration, and constant upskilling. Amid the excitement of discovering actionable insights and developing high-performing models, many wonder if it’s truly possible to maintain a healthy work-life balance. With the field evolving at breakneck speed, the intensity of these roles can leave even the most passionate data professionals drained and questioning how to protect their personal well-being. This article delves into the reality of high-intensity data science jobs, offering practical guidance on setting realistic expectations and preserving mental health. We’ll look at common pitfalls like burnout and perpetual “always learning” pressure, while also highlighting proven strategies for boundary-setting and effective time management. Whether you’re a seasoned data architect, an aspiring machine learning engineer, or somewhere in between, you’ll find actionable tips to help you manage your career trajectory without sacrificing your personal life.

From Research Labs to Real-World Insights: How Academic Researchers Can Thrive in Data Science

Over the past decade, the data science revolution has swept across industries—retailers predicting shopping habits, hospitals personalising patient treatments, and finance companies detecting fraud in near-real time. This surge in data-driven decision-making has created a pressing need for specialists capable of extracting meaningful insights from complex datasets. As a result, PhD holders and academic researchers are uniquely positioned to bring high-calibre analytical skills to the commercial realm. But transitioning from academia to data science can seem daunting: Where do you begin? How do you communicate your research background in industry-friendly terms? What new tools should you learn? This comprehensive guide, explores the paths, challenges, and strategies for academics making the leap into data science. You’ll discover how to leverage your scholarly expertise, adopt a commercial mindset, and build a career that transforms raw data into actionable insights—fostering innovations across every sector of the economy.