Quantitative Trader

Talent Corner Hr Services; Rajkot; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

Talent Corner Hr Services is seeking a Quantitative Trader to research, develop, and trade systematic strategies in Indian index futures and options. The role involves end-to-end responsibility from hypothesis generation to live deployment and post-trade analysis.

The candidate should have 2+ years in quantitative trading, strong Python with pandas/NumPy, and deep knowledge of statistics and backtesting. Relocation to Mumbai may be considered after 12–18 months.

Qualifications

• Bachelor's or Master's in a quantitative field (engineering/math/statistics/physics/computer science).
• 2+ years in quantitative trading, research, or similar roles.
• Strong understanding of options pricing, Greeks, and derivatives.
• Strong Python skills and experience with NumPy/pandas.
• Solid knowledge of statistics, time-series analysis, hypothesis testing, estimation, and model validation.

Responsibilities

• Identify, formulate, and test systematic trading hypotheses across Indian index derivatives.
• Develop predictive models for returns, volatility, and regimes using statistical/ML methods.
• Research options opportunities across strikes, expiries, volatility surfaces, and event windows.
• Build and maintain implied-vol surfaces; analyze smile, skew, and term structure.
• Develop research frameworks accounting for look-ahead bias, overfitting, costs, and regime changes.
• Take ownership of a live trading book; manage capital based on performance; monitor exposures.
• Translate research into position sizing within risk, margins, liquidity, and drawdown limits.
• Develop execution assumptions including spreads, slippage, costs, and liquidity.
• Write production-grade Python code; contribute to shared research frameworks and trading infra.

Skills

Quantitative analysis

Statistical modeling

Time-series analysis

Backtesting

Education

Bachelor's or Master's in Engineering/Math/Stats/Physics/CS

Tools

Python

NumPy

pandas

SciPy

Job description

Role & responsibilities

Quantitative Trader

Team: Systematic Trading

Location: Rajkot, Gujarat (Open to relocating to Mumbai within 12 to 18 months)

Employment: Full-time, Permanent

Level: MidSenior Reports to: Head of Trading

About the Role

We are a proprietary trading firm deploying our own capital in Indian listed derivatives. We are hiring a Quantitative Trader to research, develop, and trade systematic strategies in Indian index futures and options.

This is a P&L-owning role with end-to-end responsibilityfrom hypothesis generation and data research to back testing, live deployment, risk management, and post-trade analysis. Our trading horizon is typically minutes to several days, with an emphasis on modelling and statistical edge rather than ultra-low latency.

We are strategy-agnostic: directional, momentum, mean reversion, volatility, relative value, event-driven, calendar, and other systematic approaches are all welcome.

Role & Responsibilities

Strategy Research

• Identify, formulate, and test systematic trading hypotheses across Indian index derivatives.
• Develop predictive models for returns, volatility, market regimes, and event-driven behaviour using statistical and machine-learning techniques where appropriate.
• Research options-specific opportunities across strikes, expiries, volatility surfaces, term structure, and event windows.
• Develop and maintain implied-volatility surfaces and analyse changes in smile, skew, and term structure.
• Build research frameworks that rigorously account for look-ahead bias, overfitting, multiple testing, survivorship bias, transaction costs, and regime changes.
• Evaluate strategy robustness, scalability, and capacity, with a clear understanding of where and why an edge deteriorates.

Trading & Risk

• Take ownership of a live trading book and progressively manage capital based on demonstrated performance.
• Monitor and actively manage options exposures including delta, gamma, vega, and theta, with appropriate consideration of vanna, charm, volga, and other second-order risks.
• Translate research outputs into practical position sizing within defined risk, margin, liquidity, and drawdown limits.
• Develop realistic execution assumptions covering spreads, slippage, market impact, transaction costs, expiry-day costs, and liquidity across strikes and expiries.
• Monitor live strategy behaviour and identify deviations between model expectations and realised performance.
• Perform systematic attribution and post-trade reviews to understand both profitable and adverse periods and feed those findings back into the research process.

Quantitative Infrastructure

• Build and maintain the infrastructure required for independent research and trading.
• Work with tick-level, futures, and options-chain data, including data cleaning, feature generation, and historical reconstruction.
• Develop tools for signal generation, volatility-surface analysis, portfolio analytics, execution, and real-time risk monitoring.
• Write reliable, well-tested, production-quality Python code suitable for collaborative use.
• Contribute to shared research frameworks, libraries, analytics, and trading infrastructure.

Preferred candidate profile

Required Qualification

• Bachelor's or Master's degree in Engineering, Mathematics, Statistics, Physics, Computer Science, or a related quantitative field.
• 2+ years of experience in quantitative trading, research, or a comparable role.
• Strong understanding of options pricing, Greeks, and listed derivatives.
• Strong Python skills, including NumPy, pandas, and scientific/ML libraries.
• Solid knowledge of statistics, time-series analysis, hypothesis testing, estimation, and model validation.
• Strong understanding of back testing pitfalls and research methodology.
• Experience with Indian equity/index derivatives is highly valued.

Preferred

• IIT/NIT/ISI/IISc or comparable quantitative background.
• Experience trading Indian index futures and options.
• Experience optimizing Python for large-scale research and data processing.
• Demonstrated ability to independently develop and run systematic strategies.

Our Bar

We evaluate strategies on risk-adjusted, net-of-cost performance, with a working benchmark of Calmar 3 over a rolling 12-month period. We value robust research, honest risk assessment, and repeatable process over impressive but fragile back test numbers.

You Will Thrive Here If You

• Prefer ownership and measurable outcomes.
• Are intellectually honest about losses and drawdowns.
• Change your view when the evidence changes.
• Would rather rigorously reject nine strategies than deploy one without sufficient evidence.
• Enjoy systematic, research-driven decision-making