Quant Trader / Researcher – Options & Systematic Derivatives

Northstar Quant; Mumbai; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

Northstar Quant is seeking a Quant Trader / Researcher to design, research, backtest, and trade systematic options strategies across NSE and BSE. This is a research-to-trading role where you will own ideas end-to-end—from identifying market behaviour and developing hypotheses to backtesting, live deployment, and monitoring real P&L.

The primary focus will be on weekly index and liquid stock options, with emphasis on volatility, Greeks, expiry behaviour, market microstructure, and systematic

Qualifications

• 3-5 years of relevant experience in options trading, quantitative research or systematic derivatives trading.
• Hands-on experience trading or researching Indian options markets.
• Strong understanding of options pricing, Greeks, volatility and derivatives strategy construction.
• Good understanding of NSE/BSE market structure and weekly expiry mechanics.
• Strong Python skills with Pandas, NumPy, SciPy, scikit-learn and/or Polars.
• Strong foundation in statistics, probability, time-series analysis and quantitative modelling.
• Experience with backtesting frameworks or quantitative research infrastructure.
• Strong understanding of Sharpe ratio, drawdown, Calmar ratio, hit rate, exposure and risk-adjusted returns.
• Ability to independently take a research idea from hypothesis through backtesting and, ultimately, live deployment.

Responsibilities

• Design, backtest, and trade systematic options strategies across index and stock options.
• Research Delta, Gamma, Theta and Vega across weekly expiry cycles.
• Develop strategies around theta decay, gamma dynamics, expiry-day behaviour.
• Research implied volatility surfaces, term structure, skew, IV crush and realised-vs-implied volatility.
• Generate and evaluate signals using technical, derivatives and market-microstructure data.
• Monitor live strategy performance, risk, exposures and P&L.

Skills

Python

Pandas

NumPy

SciPy

scikit-learn

Polars

Statistics

Time-series

Backtesting

Feature engineering

Risk modelling

Tools

Backtesting frameworks

Job description

About The Role

We are looking for a Quant Trader / Researcher to design, research, backtest, and trade systematic options strategies across NSE and BSE. This is a research-to-trading role where you will own ideas end-to-end—from identifying market behaviour and developing hypotheses to backtesting, live deployment, and monitoring real P&L. The primary focus will be on weekly index and liquid stock options, with particular emphasis on volatility, Greeks, expiry behaviour, market microstructure, and systematic signal generation.

Key Responsibilities

• Design, backtest, and trade systematic options strategies across Nifty, Bank Nifty, FinNifty, Sensex and liquid stock options.
• Research the behaviour of Delta, Gamma, Theta and Vega across weekly expiry cycles.
• Develop strategies around theta decay, gamma dynamics, expiry-day behaviour, pinning and volatility dislocations.
• Research implied volatility surfaces, term structure, skew, IV crush and realised-vs-implied volatility.
• Generate and evaluate signals using technical, derivatives and market-microstructure data.
• Work with datasets including Open Interest, PCR, OI changes, basis, price/volume and intraday data.
• Use statistical modelling, time-series analysis and machine learning for signal generation, regime detection and risk-reward estimation.
• Conduct rigorous backtesting across different market regimes, time periods and volatility conditions.
• Identify overfitting, look-ahead bias, survivorship bias and other research pitfalls.
• Translate validated research into live trading strategies in collaboration with trading and technology teams.
• Monitor live strategy performance, risk, exposures and P&L and recommend improvements where required.
• Continuously research new systematic opportunities and improve existing strategies.

Required Qualifications & Skills

• 3-5 years of relevant experience in options trading, quantitative research or systematic derivatives trading.
• Hands-on experience trading or researching Indian options markets.
• Strong understanding of options pricing, Greeks, volatility and derivatives strategy construction.
• Good understanding of NSE/BSE market structure and weekly expiry mechanics.
• Strong Python skills with experience in Pandas, NumPy, SciPy, scikit-learn and/or Polars.
• Strong foundation in statistics, probability, time-series analysis and quantitative modelling.
• Experience working with large historical and/or intraday market datasets.
• Ability to clean, transform and engineer features from financial market data.
• Experience with backtesting frameworks or quantitative research infrastructure.
• Strong understanding of Sharpe ratio, drawdown, Calmar ratio, hit rate, exposure and risk-adjusted returns.
• Ability to independently take a research idea from hypothesis through backtesting and, ultimately, live deployment.
• Strong analytical thinking and attention to detail.
• Comfortable working in a fast-paced, research-driven environment.

Preferred / Good To Have

• Experience in volatility modelling or volatility trading.
• Experience with options market-making or systematic execution.
• Experience applying machine learning to trading strategies.
• Experience building a backtesting framework or research infrastructure from scratch.
• Experience with order-flow and market-microstructure signals.
• Experience trading or researching expiry-day strategies.
• Familiarity with high-frequency or tick-level data.

What We Offer

• Opportunity to work on systematic strategies across some of the world’s most liquid derivatives markets.
• Direct ownership of research ideas that translate into live positions and real P&L.
• Exposure to quantitative research, live trading, technology and risk management.
• A high-performance environment that values rigorous research over shortcuts.
• Opportunity to work closely with experienced traders, researchers and technologists.
• Scope to build and influence Northstar’s systematic trading capabilities from the ground up.

Ideal Candidate

The ideal candidate is not just a trader or just a researcher. We are looking for someone who understands options deeply, thinks quantitatively, can code and backtest independently, and is comfortable taking ownership from idea → research → validation → live strategy → performance monitoring.

Location: Mumbai

Experience: 3-5 years

Function: Quantitative Trading / Research

Employment: Full-Time

Skills: trading, backtesting, research, derivatives