Quantitative researcher

Job Overview
We are seeking curious and creative quantitative researchers to join our rapidly growing team. You will dive into the core of financial data, responsible for the whole closed loop from signal research, model construction to strategy implementation. You need solid mathematical statistics, excellent programming skills, and a deep intuitive understanding of the financial market microstructure. This is an excellent opportunity to directly translate your academic wisdom into commercial influence.

Core responsibilities

1. Strategy research and development: Independently or collaboratively conduct Alpha factor/signal research, mining and testing, covering stocks, futures, options or other asset classes.

2. Model building and optimization: Develop and continuously optimize multi-factor models, prediction models, trading execution algorithms or risk management models.

3. Full process validation: Design a rigorous backtesting framework, backtest strategies using historical data, out-of-sample testing and performance attribution analysis, and ensure their robustness and generalizability.

4. Data processing: Process and analyze massive structured and unstructured data (such as volume data, fundamental data, alternative data, etc.), ensure data quality and research reliability.

5. Close collaboration: Work closely with quantitative developers and trading engineers to translate research models into efficient, low-latency production code that can run in a live trading environment.

6. Frontier Exploration: Continuously track the latest research findings from academia and industry, explore new data sources, models and methodological approaches.

Job Requirements
Must-haves:

1. Educational background: Master's or doctoral degree from top domestic and international universities, majoring in but not limited to: Computer Science, Statistics, Mathematics, Physics, Financial Engineering, Electronic Engineering, etc. highly quantitative fields.

2. Mathematical and physical foundations: Solid foundation in probability theory, mathematical statistics, time series analysis, machine learning, and optimization theory.

3. Programming skills: Proficient in Python, familiar with NumPy, pandas, scikit-learn, statsmodels, etc., scientific computing and data analysis libraries. Have good coding conventions.

4. Research ability: Have strong logical thinking, critical thinking and problem solving skills, and be able to conduct rigorous scientific research independently.

5. Basic qualities: Strong interest and enthusiasm for financial markets, result-oriented, with strong self-motivation, sense of responsibility, and team spirit.

Priority (with the following experience preferred) :

1. In relevant internships or work experience at well-known quantitative institutions.

2. Having solid financial knowledge, understanding the pricing and risks of stocks, futures, options, etc. products.

3. Have experience in high-performance computing, big data processing (such as Spark) or databases (such as SQL).

5. Have published related papers in international top journals/conferences, or have achieved excellent results in well-known quantitative competitions (such as Kaggle, ACM-ICPC, various quantitative competitions in China)

We provide

1. Top salary and benefits

2. Pure research environment: Flat management, focusing on solving interesting and challenging practical problems, and avoiding unnecessary bureaucracy.

3. Strong infrastructure: Access massive, high-quality data sources, as well as high-performance computing cluster support, to quickly validate your ideas.

4. Professional development: Clear career development path (researcher -> senior researcher -> investment manager/team leader), as well as the opportunity to work and learn from industry top talents.

5. Benefits and security