Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Quantitative Developer

Tower Research Capital
City of London
3 days ago
Create job alert

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.

Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities
Tower Research Capital seeks a Quantitative Developer to join the Core Engineering team to help build out our Quantitative Execution Services. You will be closely working with researchers and traders on the Central Execution Desk, directly contributing to scale up Tower's Mid-Frequency Trading capabilities.

  • Design, implement, and maintain high-performance services in Rust and Python for market-data ingestion, ML pipelines, and post-trade analytics
  • Translate research prototypes into production-ready code, adding testing, monitoring, and CI/CD automation
  • Optimise existing code for throughput, memory footprint, and reliability on distributed systems
  • Collaborate closely with quantitative researchers to iterate on data pipelines, simulation frameworks, and performance diagnostics

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related STEM field
  • 2-5 years of professional software-engineering experience, including production systems written in Python
  • Proficiency in a systems language - Rust preferred (C++/Go also acceptable) - and the desire to deepen that expertise
  • Strong computer-science fundamentals: algorithms, data structures, concurrency, networking, and performance profiling
  • Experience working with real-time and historical market data or other high-volume time-series data
  • Proficiency with Linux development, Git, containers, and CI/CD workflows
  • Familiarity with SQL and at least one columnar or time-series data store (e.g., kdb+, ClickHouse, InfluxDB, Parquet/Arrow)
  • Excellent problem-solving abilities, attention to detail, and clear communication skills

Nice To Have:

  • Prior exposure with execution algos, TCA, order-routing, or market-impact modelling
  • Knowledge of statistical or machine-learning libraries (NumPy, pandas, scikit-learn, PyTorch)
  • Experience building distributed systems with message buses (Kafka, ZeroMQ) and asynchronous I/O
  • Experience with cloud or on-prem orchestration and scheduling frameworks (Kubernetes, HT Condor, SLURM)

Benefits

Tower’s headquarters are in the historic Equitable Building, right in the heart of NYC’s Financial District and our impact is global, with over a dozen offices around the world.

At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive – without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.

Our benefits include:

  • Generous paid time off policies
  • Savings plans and other financial wellness tools available in each region
  • Hybrid working opportunities
  • Free breakfast, lunch and snacks daily
  • In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
  • Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
  • Volunteer opportunities and charitable giving
  • Social events, happy hours, treats and celebrations throughout the year
  • Workshops and continuous learning opportunities

At Tower, you’ll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work – together.

Tower Research Capital is an equal opportunity employer.


#J-18808-Ljbffr

Related Jobs

View all jobs

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.