استخدام Quantitative Analyst_Junior/Mid-Level

About Hermes Capital
Hermes Capital is a quantitative trading and financial technology firm developing systematic trading
strategies in Iran's financial markets. We combine statistical research, financial modeling, and software
engineering to identify market inefficiencies and build automated trading systems.

About the Role

We are looking for a Junior / Mid-Level Quantitative Analyst to join our research team. You will work with real-world financial data to investigate market behavior, develop quantitative models, evaluate trading strategies, and identify opportunities for improvement.

We value strong analytical thinking, curiosity, and a systematic approach to problem-solving. Prior professional experience in quantitative trading is not required.

Key Responsibilities

• Analyze financial time series, trading activity, and order book data to identify market patterns and inefficiencies.

• Develop statistical models for pricing, forecasting, and trading decisions.

• Design experiments, test hypotheses, and evaluate the reliability of quantitative signals.

• Backtest trading strategies, accounting for risk, liquidity, and transaction costs.

• Investigate existing strategies and propose data-driven improvements.

• Collaborate with researchers and engineers to translate research findings into practical trading solutions.

Required Qualifications

• Proficiency in Python for data analysis (NumPy, Pandas).

• Familiarity with SQL and working with structured datasets.

• Strong foundations in probability, statistics, and mathematics.

• Understanding of statistical methods, including regression and hypothesis Testing.

• Strong analytical reasoning, problem-solving, and research skills.

• Ability to work independently and communicate findings clearly.

• Interest in financial markets, quantitative research, and algorithmic trading.

Nice to Have

• Knowledge of quantitative finance, financial time series, or econometrics.

• Familiarity with market microstructure, order books, and liquidity.

• Experience with machine learning, Optimization, or statistical modeling.

• Experience with SciPy, Statsmodels, scikit-learn, or CVXPY.

• Familiarity with ClickHouse, Streamlit, or Grafana.

• Relevant academic, personal, or professional research projects.

What We Offer

• Work on challenging, real-world quantitative trading problems.

• Hands-on experience with financial data, modeling, and strategy development.

• Collaboration with experienced researchers and software engineers.

• Opportunities to turn research ideas into live trading systems.

• A learning-oriented environment with increasing research ownership.

Join Us

If you enjoy solving complex analytical problems, questioning assumptions, and applying mathematics and data analysis to financial markets, we'd love to hear from you