Verified Job
IT / Software / Data Analyst
Quantitative Research Analyst
IT / Software / Data Analyst
#1685
Remote / WFH
Univest ·
Job Description
Department: Algo Trading / TradeZapp
Location: Gurugram, Haryana (Hybrid)
Reports To: CEO
Experience: 3–5 years in systematic / algorithmic trading
Employment Type: Full-Time
MUST-HAVE QUALIFICATIONS
• 3–5 years of hands-on experience in systematic or algorithmic trading (buy-side or prop desk
preferred)
• Strong understanding of Indian equity markets — NSE F&O, expiry cycles, Open Interest
dynamics, PCR interpretation
• Deep working knowledge of options pricing — Black-Scholes, Greeks, IV surface, volatility skew
• Proficient in Python (pandas, numpy, scipy) — able to independently write and audit backtest
code
• Experience designing and backtesting multi-factor alpha models
• Understands backtest pitfalls — look-ahead bias, survivorship bias, overfitting
GOOD-TO-HAVE QUALIFICATIONS
• CFA / FRM / NISM Series VIII (Equity Derivatives) certification
• Experience at a prop trading firm, hedge fund, or quant desk at a brokerage
• Published research on Indian market microstructure or options strategies
• Familiarity with signal frameworks — Stochastic RSI, CMF, OBV, Smart Money Concepts (SMC)
• Exposure to GARCH models, regime-switching volatility, or advanced IV estimation techniques
KEY RESPONSIBILITIES
• Refine and evolve the 5-signal regime model — add/remove indicators, tune weights, improve
conviction scoring
• Design better Implied Volatility estimation methods (e.g., replace rolling realised vol with GARCH
or regime-switching vol)
• Improve options strike selection logic — move from fixed OTM distance to dynamic selection
based on IV regime
• Build delta-hedging and rolling logic for options positions
• Define stress scenarios and edge cases for the risk engine
• Own all 21 backtest scenarios, interpret results, and translate findings into actionable model
changes
• Collaborate with the engineering team to productionise validated strategies
• Continuously research and integrate new alpha sources and signal enhancements
TECH & TOOLS
• Python (pandas, numpy, scipy, statsmodels), Jupyter Notebooks
• Node.js / Express (production signal engine)
• Kite Connect v3 API (Zerodha) for market data and execution
• Backtesting frameworks and quantitative analytics tools
• Pine Script (TradingView) for visual strategy prototyping
Location: Gurugram, Haryana (Hybrid)
Reports To: CEO
Experience: 3–5 years in systematic / algorithmic trading
Employment Type: Full-Time
MUST-HAVE QUALIFICATIONS
• 3–5 years of hands-on experience in systematic or algorithmic trading (buy-side or prop desk
preferred)
• Strong understanding of Indian equity markets — NSE F&O, expiry cycles, Open Interest
dynamics, PCR interpretation
• Deep working knowledge of options pricing — Black-Scholes, Greeks, IV surface, volatility skew
• Proficient in Python (pandas, numpy, scipy) — able to independently write and audit backtest
code
• Experience designing and backtesting multi-factor alpha models
• Understands backtest pitfalls — look-ahead bias, survivorship bias, overfitting
GOOD-TO-HAVE QUALIFICATIONS
• CFA / FRM / NISM Series VIII (Equity Derivatives) certification
• Experience at a prop trading firm, hedge fund, or quant desk at a brokerage
• Published research on Indian market microstructure or options strategies
• Familiarity with signal frameworks — Stochastic RSI, CMF, OBV, Smart Money Concepts (SMC)
• Exposure to GARCH models, regime-switching volatility, or advanced IV estimation techniques
KEY RESPONSIBILITIES
• Refine and evolve the 5-signal regime model — add/remove indicators, tune weights, improve
conviction scoring
• Design better Implied Volatility estimation methods (e.g., replace rolling realised vol with GARCH
or regime-switching vol)
• Improve options strike selection logic — move from fixed OTM distance to dynamic selection
based on IV regime
• Build delta-hedging and rolling logic for options positions
• Define stress scenarios and edge cases for the risk engine
• Own all 21 backtest scenarios, interpret results, and translate findings into actionable model
changes
• Collaborate with the engineering team to productionise validated strategies
• Continuously research and integrate new alpha sources and signal enhancements
TECH & TOOLS
• Python (pandas, numpy, scipy, statsmodels), Jupyter Notebooks
• Node.js / Express (production signal engine)
• Kite Connect v3 API (Zerodha) for market data and execution
• Backtesting frameworks and quantitative analytics tools
• Pine Script (TradingView) for visual strategy prototyping
