Quant Trader / Researcher – Options & Systematic Derivatives

Northstar Quant; Maharashtra; Vor Ort; INR 4.000.000 - 9.000.000; Vollzeit

Benefits dieser Stelle

Own research ideas

Live P&L exposure

Collaborative team

High-performance environment

Zusammenfassung

Northstar Quant is seeking a Quant Trader/Researcher to design, backtest, and trade systematic options strategies across NSE/BSE. This research-to-trading role will own ideas end-to-end—from hypothesis to live deployment and monitoring P&L.

Focus will be on weekly index and liquid stock options, volatility, Greeks, and expiry dynamics. Ideal candidates have 3–5 years in options trading or quantitative research, strong Python skills (Pandas, NumPy, SciPy, scikit-learn), and a solid grounding in

Qualifikationen

• 3–5 years of relevant experience in options trading or quantitative research.
• Hands-on experience with Indian options markets.
• Strong understanding of options pricing, Greeks and derivatives.
• Knowledge of NSE/BSE market structure and weekly expiry mechanics.
• Proficient in Python data stack and statistical modelling.

Aufgaben

• Design, backtest, and trade systematic options strategies.
• Research Delta, Gamma, Theta and Vega across weekly expiry cycles.
• Develop strategies around theta decay, expiry-day behaviour and volatility.
• Generate signals using technical and market microstructure data.
• Backtest across regimes and monitor live strategy performance.

Kenntnisse

Python

Quant research

Backtesting

Statistics

Market microstructure

NSE BSE

Ausbildung

MSc/BE/Math

Tools

Pandas

NumPy

SciPy

scikit-learn

Polars

Jobbeschreibung

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

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: research,trading,derivatives,backtesting