Software Expert (Scientific Computing)
Job Description
Scientific discovery and data-driven insights increasingly rely on robust computational tools. As a Software Expert (Scientific Computing), you will empower AI to generate accurate, efficient, and reliable code for numerical methods, statistical analysis, and complex scientific simulations, accelerating research across disciplines.
Key Responsibilities
Evaluate AI-generated code for scientific computing tasks, ensuring mathematical correctness and numerical stability.
Review implementations using libraries like NumPy, SciPy, and Pandas for data manipulation, statistical analysis, and linear algebra.
Assess AI's ability to generate code for advanced numerical methods, including differential equations, optimization, and signal processing.
Create high-quality training data for statistical modeling, hypothesis testing, and data visualization in Python and R.
Debug and optimize AI-generated scientific code for performance, memory efficiency, and parallelization.
Provide expert feedback on AI's understanding of domain-specific scientific principles and best practices in computational science.
Ideal Qualifications
7• years of experience in scientific computing, computational science, or quantitative research.
Expert proficiency in Python with extensive experience using NumPy, SciPy, Pandas, and Matplotlib.
Strong experience with R for statistical analysis and data visualization.
Deep understanding of numerical methods, linear algebra, calculus, and statistics.
Familiarity with parallel computing frameworks (e.g., Dask, MPI) and GPU acceleration (e.g., CuPy) is a plus.
Experience with data visualization tools and libraries (e.g., Seaborn, Plotly).
Project Timeline
Start Date: Within 1-2 weeks
Duration: 6 months, with potential for extension
• Commitment: 20-30 hours/week
Advance scientific breakthroughs by refining AI's computational prowess!