量化实习生（香港）

该职位来源于猎聘

此岗位base香港，面向香港在校生 Responsibilities

• Participate in the research, design, and development of quantitative trading strategies and models. Explore how derivatives such as options can be used to optimize risk-return profiles and reduce volatility.
• Participate in the research, evaluation, and continuous optimization of alpha signals, including factor validation, signal blending, stability testing, and out-of-sample performance analysis.
• Assist in portfolio analysis and portfolio construction, covering portfolio optimization, risk budgeting, position sizing, factor-exposure analysis, correlation analysis, and risk-return attribution.
• Support the processing, cleaning, and analysis of multi-dimensional financial data, and extract investment-relevant signals from market, fundamental, and alternative data.
• Assist in the continuous optimization and iteration of existing quantitative models, research frameworks, and analytical tools.
• Help develop return, risk, and portfolio-analysis tools to support investment and trading decision-making.
• Build research, backtesting, and data-processing pipelines using Python and relevant data analytics libraries; leverage AI tools to improve efficiency in research, programming, and data analysis.
• Provide additional support to the team on quantitative research, asset allocation, portfolio management, and trading-related tasks. Requirements
• Degree in a STEM or quantitative-related discipline, such as Mathematics, Physics, Statistics, Computer Science, or Financial Engineering. Strong academic foundation with an outstanding record.
• Strong Python programming skills for data processing, statistical analysis, model development, and backtesting; proficient with common data analytics libraries such as pandas and NumPy.
• Capable of effectively applying AI tools to assist with programming, research, data analysis, and information synthesis, with the ability to verify and critically assess AI-generated output.
• Strong data processing and analysis skills; prior experience with financial data is preferred.
• Basic knowledge of alpha research, factor research, portfolio analysis, portfolio construction, or asset allocation is preferred.
• Familiarity with option pricing, volatility trading, derivative strategies, or portfolio risk management is preferred.
• Knowledge of machine learning, time-series analysis, statistical modeling, or optimization algorithms is preferred.
• Hands-on mindset, ability to maintain sustained focus, and work efficiently. Strong team player with a meticulous and pragmatic working style, strong self-motivation, and innovative thinking.