Quantitative Trading Analyst - Commodities

About the Role and Company

Summit Dairy is an established commodity trading firm specializing particularly in soft commodities. We leverage data-centric approaches, in-depth market analytics, and engage actively on global commodity exchanges like CME and ICE. Our team values curiosity, rigorous analytical thinking, and solution-oriented mindsets.

We are hiring a Quantitative Trading Analyst based in Hyderabad, India. This full-time position entails working during American market hours (approx. 2:30 to 12:30 AM IST) to synchronize with trading operations.

Responsibilities

• Develop quantitative models to forecast commodity prices, assess spread relations, volatility, and seasonal trends in agricultural commodities.
• Utilize time-series analyses and regression fundamentals to underpin models.
• Model supply and demand by integrating data from production, trade flows, inventories, and weather metrics.
• Create, back-test, and stress-test both systematic and discretionary trading signals.
• Validate hypotheses drawing from both structured and unstructured datasets.
• Draft market commentaries, reports, and perform ad-hoc analyses to inform traders and management.
• Assess strategy outcomes regularly to optimize models and procedures.
• Monitor market conditions, open positions, and risk metrics related to the trading desk.
• Stay updated on scheduled economic and market releases, as well as impactful news events.
• Assist traders by verifying quantitative assumptions through modeling.

Candidate Requirements

• Bachelor's or master's degree in Statistics, Econometrics, Mathematics, Quantitative Economics, Financial Engineering, or comparable quantitative fields, preferably from a leading institution.
• Experience of 2 to 4 years in quantitative research, econometric modeling, risk analysis, or related trading analytics; highly capable recent graduates may be considered.
• Exposure to commodity futures or options markets is advantageous but not compulsory.
• Strong foundation in probability theory, statistical inference, econometrics methods including regression diagnostics, time series analysis, and hypothesis testing.
• Proficiency in Python programming for data analysis and model development; knowledge of R or MATLAB is an added advantage.
• Experience in managing financial time series data and constructing back-tests that avoid look-ahead or survivorship biases.
• Excellent communication skills to translate quantitative output effectively to trading teams and senior management.
• Intellectual honesty in acknowledging model limitations and adapting swiftly.
• Self-motivated, resilient under pressure, and collaborative mindset.
• Demonstrated enthusiasm and aspiration to influence profit and loss directly through trading activities.