该职位来源于猎聘 Roles And Responsibilities
- Design and develop computational finance applications with a focus on performance, scalability, and accuracy.
- Implement high-performance and parallel computing solutions to optimize computationally intensive tasks.
- Collaborate with actuarial teams to integrate financial models and simulations into scalable software systems.
- Write clean, efficient, and maintainable code using best software engineering practices.
- Conduct performance analysis, profiling, and optimizations to improve system throughput and latency.
- Architect software systems that are modular, extensible, and maintainable
- Design and implement APIs and libraries to support financial calculations and simulations.
- Document technical decisions, development processes, and optimization results.
- Keep up to date of emerging trends and technologies in high-performance computing, parallel processing.
Job Requirements
- Technical field Bachelor's / Master degree (e.g. Computer Engineering or Computer Science)
- 10+ years software engineer experience in developing / launching products, libraries and technologies within the actuarial / financial industry.
- With Technical Lead experience, having led 5+ developers' team and driven projects for whole life cycle.
- Proficiency in programming languages like, Python, C++ or Java , with a focus on performance optimization.
- Solid understanding of data structures, algorithms, and software design patterns.
- Strong experience in parallel programming or distributed systems (e.g. CUDA).
- Strong experience in GPU programming, vectorization, or other hardware acceleration techniques.
- Familiarity with multithreading, concurrency, and asynchronous programming.
- Experience in the Agile methodologies and software development life cycle (SDLC), including requirements gathering, design, implementation, testing, and deployment.
- Experience in profiling, debugging, and optimizing code for performance.
- Hands-on experience with cloud-based platforms (AWS, GCP, Azure) for scalable computing solutions.
- Knowledge of version control tools (e.g. Git) and CI/CD workflows. Preferred Experience
- Experience developing software on Linux
- Familiarity with QuantLib or similar quantitative finance libraries
- Prior experience developing applications in computational finance, quantitative modelling, or risk analysis
- Hands-on experience with numerical libraries (e.g., NumPy, SciPy) and tools for financial simulations
- Knowledge of modern frameworks for distributed systems like, Dask or Spark