Equity Market Neutral Researcher (Mumbai)

About the Role We are looking for a Quantitative Equity Market Neutral Researcher to research, develop, and deploy systematic long-short equity strategies. The ideal candidate should have live experience generating multiple high-quality alpha signals across diverse datasets, and preferably experience managing live P&L; as a portfolio manager or senior researcher. This role requires the ability to build robust, cost-aware, regime-sensitive alpha portfolios that can perform across market cycles. Key Responsibilities - Research and develop systematic long-short equity alpha signals. - Generate alpha ideas using various kinds of standard market data, fundamental data and other alternate datasets. - Build, backtest, validate, and monitor alpha signals with rigorous controls for overfitting, data leakage, turnover, transaction costs, liquidity, and capacity. - Combine multiple alpha signals into robust portfolios using sound portfolio construction, risk modelling, signal weighting, and alpha allocation techniques. - Develop market-neutral, sector-neutral portfolio frameworks. - Analyse live performance, alpha decay, drawdowns, factor exposures, regime behaviour, and signal crowding. - Improve portfolio robustness through diversification across alpha families, holding periods, datasets, and economic hypotheses. - Work closely with engineering and data teams to move research from prototype to production. - Build tools for live monitoring, attribution, risk diagnostics, alpha health checks, and portfolio-level decision support. Required Qualifications - 5+ years of experience in quantitative equity research, preferably in equity market neutral, statistical arbitrage or systematic long-short. - Proven experience generating multiple live alpha signals with strong out-of-sample and live performance. - Strong understanding of equity market neutral portfolio construction, risk models, factor neutrality, beta hedging, turnover control, and transaction-cost-aware optimization. - Experience working with various kinds of standard and alternative datasets. - Ability to evaluate alphas across IC, hit rate, decay, capacity, drawdown, correlation, regime sensitivity, and live P&L; contribution. - Strong programming skills in Python, C++, R, or a similar language. - Solid statistical foundation across time-series analysis, cross-sectional modelling, regression, ML methods, portfolio optimization, and empirical asset pricing. - Undergrad or postgrad in Engineering, Mathematics, Statistics, Economics, Finance, Econometrics, Computer Science or a related quantitative field. Preferred Qualifications - Experience running live P&L; as a portfolio manager, pod lead, or senior researcher. - Experience at a market-neutral hedge fund, proprietary trading firm, quant asset manager, or systematic investment platform. - Demonstrated ability to combine multiple weak and partially correlated alphas into robust production portfolios. - Familiarity with regime detection, alpha timing, meta-labelling, online learning, Bayesian shrinkage, ensemble methods, or robust optimization. - Experience building medium-frequency strategies with realistic slippage and holding-period assumptions. - Understanding of factor crowding, alpha decay, drawdown clustering, and live model monitoring. What Were Looking For - A hands-on quant researcher who has created signals that have worked in live trading, not just in backtests. - Someone who can think from first principles about why an alpha should exist, when it should work, and when it should fail. - A researcher who understands that production market-neutral investing requires more than finding signals: it requires robust validation, cost control, risk management, portfolio construction, and live monitoring. - A self-starter with strong ownership mindset, intellectual honesty, and the ability to diagnose why strategies are underperforming. - A collaborative team player who can work closely with researchers, data engineers, software engineers, and portfolio managers to take research into production. .