Graduate Quantitative Research Intern: Low-Latency Trading

Tokka Labs; Singapore; On-site; SGD 20,000 - 33,000; Full time

Job summary

Tokka Labs, a proprietary trading firm, seeks a Graduate Quantitative Research Intern with a strong background in applied mathematics to tackle large-scale, low-latency problems. You will bridge optimization theory and high-performance execution, designing algorithms, analyzing methods, and building backtesting dashboards. Preference for Masters/PhD candidates in quantitative fields. Based in Singapore.

Qualifications

• Currently pursuing a Masters or PhD in Applied Mathematics, Electrical Engineering, Computer Science, Physics or a related quantitative field.
• Strong grounding in numerical analysis, real analysis, numerical optimization, probability, graph theory, numerical linear algebra, signal processing.
• Hands-on experience coding algorithms in Python, C++, or Rust, plus familiarity with optimization libraries or solvers (e.g., SciPy, NetworkX, Gurobi, OR-Tools).
• Proven ability to dissect complex theoretical problems and communicate technical concepts clearly.

Responsibilities

• Algorithm Development: Design, test, and refine pathfinding algorithms to improve execution speed and routing reliability.
• Mathematical Analysis: Provide rigorous analytical evaluations of optimization methods and models, including convergence and complexity analyses.
• Benchmarking & Backtesting: Build backtesting frameworks and dashboards to compare methods against benchmarks.
• Production Integration: Collaborate with developers to translate research prototypes into low-latency, scalable implementations.
• Advanced Research: Explore novel graph challenges to ensure system robustness.

Skills

Python

C++

Rust

Numerical optimization

Graph theory

Education

Masters/PhD in Applied Mathematics or related quantitative field

Tools

SciPy

NetworkX

Gurobi

OR-Tools

Job description

Tokka Labs, a proprietary trading firm, seeks a Graduate Quantitative Research Intern with a strong background in applied mathematics to tackle large-scale, low-latency problems. You will bridge optimization theory and high-performance execution, designing algorithms, analyzing methods, and building backtesting dashboards. Preference for Masters/PhD candidates in quantitative fields. Based in Singapore.