Quantitative Developer

This role is for one of the Weekday's clients

Quantitative Developer

Python

Requirements

Key Responsibilities

• Design, develop, and maintain quantitative models, algorithms, and analytical tools used for pricing, trading, and risk management.
• Collaborate with quants, researchers, and traders to translate business requirements into efficient and scalable technical solutions.
• Build robust data pipelines to source, clean, and process large volumes of structured and unstructured financial data.
• Implement and optimize backtesting frameworks to evaluate the performance of trading strategies.
• Enhance existing quantitative libraries and contribute to the continuous improvement of codebase, documentation, and testing standards.
• Conduct exploratory data analysis, statistical modeling, and feature engineering for research and production use.
• Integrate quantitative models and analytical outputs into trading and risk management systems.
• Stay updated on new techniques, technologies, and best practices in quantitative finance, data science, and software development.
  

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative discipline.
• 1-4 years of experience in quantitative development, data engineering, or financial modeling, preferably in a trading, research, or analytics environment.
• Strong programming proficiency in Python, including experience with libraries such as NumPy, Pandas, SciPy, and scikit-learn.
• Familiarity with object-oriented programming, data structures, algorithms, and software design principles.
• Experience with data visualization tools (e.g., Matplotlib, Plotly, Seaborn) and version control systems (Git).
• Solid understanding of statistics, probability, and numerical methods used in quantitative finance.
• Working knowledge of SQL or other database query languages.
• Ability to write clean, maintainable, and well-documented code.
• Strong problem-solving skills, analytical mindset, and attention to detail.
  

Preferred Skills

• Exposure to financial markets, trading systems, or quantitative research.
• Familiarity with machine learning techniques and frameworks such as TensorFlow or PyTorch.
• Experience with Linux environments, cloud platforms (AWS/GCP), or distributed computing frameworks.
• Understanding of time-series analysis, portfolio optimization, or risk modeling