一面千识 Hiring! Part Time Quantitative Research Expert — Task Design - Evaluation in - Ricebowl

Company: Meetchances

Employment type: Part-time

Compensation: RMB 200–500 per hour

Project period: Through December 31, 2026

Meetchances is looking for experienced quantitative finance practitioners and researchers to design and evaluate professional tasks based on realistic research scenarios.

Experts may contribute in one or more areas, including quantitative research, factor research, multi-factor models, asset pricing, portfolio construction, quantitative strategy research, financial data analysis, risk modeling, derivatives pricing, and options research.

• Design professional tasks based on realistic research scenarios in areas such as factor research, asset pricing, strategy research, portfolio construction, risk analysis, and derivatives pricing.
• Organize research materials, including market and trading data, financial data, factor data, macroeconomic data, portfolio data, backtest results, research reports, model parameters, and strategy code.
• Define research criteria and acceptance standards, including data scope, sample periods, factor definitions, model assumptions, backtesting and validation methods, evaluation metrics, risk constraints, and result interpretation criteria.
• Review quantitative research outputs for accuracy and sound reasoning. Identify issues such as data processing errors, look-ahead bias or data leakage, factor definition errors, unreasonable model assumptions, overfitting, distorted backtests, weak statistical robustness, and overlooked risks.

• At least one year of cumulative internship experience in a relevant quantitative research area, or relevant full-time work experience.
• Able to independently complete data processing, research design, model analysis, backtesting, and result interpretation in at least one relevant area.
• Strong expertise in at least one quantitative research area, with the ability to explain the research objective, data sources, core assumptions, model or factor construction, validation methods, evaluation metrics, and key risks.
• Able to make evidence-based professional judgments from financial data, model outputs, and backtest results, with clear reasoning and appropriate risk boundaries.

Students are welcome to apply if they have substantial, ongoing internship experience in a relevant quantitative research area and meet the experience requirement.