Job Description

Key Responsibilities:

• Systematic Strategy Development: Be able to design and implement rule based Positional Equity Strategies using Python, incorporating advanced regime-switching filters, volatility conditioning, and momentum factors to navigate diverse market cycles
• Be able to undertake Quantitative Research by using Multi factor model development, Statistical & ML Methods, Quantamental Strategy Integration, Alternative Data Analysis & AI Automation for all asset classes across multiple economic regimes
• Alpha Research: Be able to conduct deep dive research into factor momentum and volatility descriptors to optimize entry / exit timing and enhance alpha generation across different market cycles
• Back Testing & Validation: Develop automated frameworks to back test strategies (e.g. Trend following or Mean reversion) using multi – year historical data to ensure statistical significance and robust drawdown protection
• Sector Leadership Identification: Utilize Relative Rotational Graphs (RRG), Ratio Charts, and Relative Strength Models to identify sectoral shifts and provide a “top – down” view for institutional capital allocation and to identify structural shifts and outperformers
• Global Macro – Technical Integration: Perform inter market co relation analysis (Commodity, Currency, Bond Yields & Equity Markets) to provide actionable insights from both a short-term trading and long-term investment perspective into the equity markets
• Pattern Recognition: Develop time series algorithms to detect complex technical patterns in Equities, Futures & fixed Income, translation raw price action into actionable data – driven insights
• Also, be able to develop understanding of quantitative trading models, focusing on approaches tailored to equities, and derivatives across global markets & develop algorithms to detect patterns in Price action & time series for equity markets, enabling data driven insights for trading focusing on trend following, momentum and range bound behavior
• Dynamic Hedging Solutions: Provide data-driven hedging recommendations using F&O Greeks and correlation – based pair trades to protect institutional portfolios during high volatility events
• Optimization & Attribution: Lead the construction of multi asset portfolios using quantitative fundamental research, ensuring rigorous Trade Level Attribution and benchmark – relative performance evaluation
• Increasing Efficiency by usage of Big Data: Be able to build and maintain automated data pipelines and live feed integrations using Python (& other languages), Bloomberg, and Trendlyne, aiming to reduce research cycle times & increase efficiency in using big data
• Screener Development: Design proprietary Techno-Funda screeners to eliminate manual scanning, providing real – time alerts on high probability institutional setups
• Thematic Research: Transform “Big Data” crunching into high conviction Sectoral Thematic reports, offering a unique edge to institutional desks
• Institutional Advisory: Act as a subject matter expert in client webinars and investor awareness sessions, translating complex quantitative output into high – impact presentation materials and pitch desks

More Info

Education