Quant Researcher Commodities MFT

Position: Quantitative Researcher – Commodities, MFT (Neo Markets)

Summary

As a Quantitative Researcher on our Medium-Frequency Trading (MFT) desk, you will be responsible for researching, developing and deploying systematic trading strategies in commodity futures and options, with a primary focus on MCX. The ideal candidate combines strong statistical and Python skills with a solid understanding of commodity market dynamics and will work closely with traders and developers to take ideas from research to live trading.

Job Responsibilities

The position holder shall be responsible for

• Research, develop and implement systematic mid-frequency trading strategies in commodity futures and options, with a primary focus on MCX energy, base metals and bullion contracts
• Conduct alpha signal research using statistical techniques, time-series analysis and machine learning across intraday to multi-day horizons
• Model commodity-specific drivers such as term structure, calendar and inter-commodity spreads, rollover dynamics, seasonality, inventory and macro data releases
• Analyse the relationship between MCX contracts and international benchmarks (CME/NYMEX, COMEX, LME), including the impact of USD-INR movements, to identify trading opportunities
• Build predictive models for price movement, volatility and liquidity, and develop volatility and pricing models for commodity options
• Work with large-scale structured and unstructured datasets (tick, bar and order book data, along with fundamental and alternative data), ensuring data quality and integrity
• Design robust backtesting frameworks in Python with realistic assumptions for transaction costs, slippage, liquidity, contract rollovers and exchange-specific constraints such as trading hours, daily price ranges and margins
• Evaluate strategy performance using metrics such as Sharpe ratio, Calmar ratio, drawdown, hit rate, turnover and PnL attribution, and conduct parameter optimization, robustness checks and stress testing
• Collaborate with traders and developers to take strategies from research into production
• Monitor live strategies, analyse realised versus expected performance, and refine models based on live feedback
• Manage strategy-level risk, including position sizing, capacity analysis and portfolio construction across commodities

Knowledge, Competency and Skills requirement

• Bachelor’s / Master’s / PhD in Mathematics, Statistics, Computer Science, Physics, Engineering, Economics or a related quantitative field
• 3 years of experience in quantitative research or systematic trading is preferred
• Strong programming skills in Python (mandatory), with experience in NumPy, Pandas, SciPy, statsmodels and scikit-learn
• Familiarity with version control (Git)
• Experience handling and processing large time-series datasets; working knowledge of SQL
• Solid understanding of probability and statistics, linear algebra, optimization and time-series analysis
• Good understanding of futures and options, including term structure, basis, rollovers, option pricing and Greeks
• Passion for financial markets, particularly commodities
• Strong analytical and problem-solving skills
• Ability to adapt to a dynamic work environment and show exceptional prowess at managing large impact situations
• Keen to learn, hungry for growth
• Flexibility to work independently and as a part of the team

Preferred Skills

• Experience researching and trading commodities, particularly on MCX
• Exposure to international commodity markets (CME/NYMEX, COMEX, LME) and their linkages with domestic prices
• Prior experience at a proprietary trading firm, hedge fund or systematic trading desk running MFT strategies
• Experience running trading strategies in production with PnL responsibility
• Experience with commodity options and volatility trading
• Participation in competitive programming / Kaggle / quant competitions