We are seeking a highly analytical Quantitative Research Analyst to join our AIF Quant Fund team.The ideal candidate brings strong buy-side experience in systematic investment strategies and will play a key role in developing, implementing, and maintaining sophisticated quantitative models that drive our alternative investment approach.
About The Role
The Quantitative Research Analyst will be responsible for various key responsibilities that include model development, data infrastructure management, strategy testing, risk management, and technology :
Model Development & Research
- Design and build multi-factor models for equity, fixed income, and alternative asset classes.
- Develop alpha generation signals and systematic trading strategies across multiple time horizons.
- Research and implement new quantitative factors using academic literature and market insights.
- Enhance existing models through continuous performance monitoring and iterative improvements.
Data Infrastructure & Analytics
- Manage large-scale financial datasets using Snowflake, SQL, and cloud-based platforms.
- Build automated data pipelines for real-time and historical market data processing.
- Ensure data quality, integrity, and optimize query performance for research workflows.
- Develop efficient storage solutions for multi-asset research environments.
Strategy Testing & Validation
- Conduct comprehensive back testing across multiple market cycles using robust statistical methods.
- Perform out-of-sample testing, walk-forward analysis, and Monte Carlo simulations.
- Generate detailed performance attribution and risk decomposition analysis.
- Document model assumptions, limitations, and validation results.
Risk Management & Monitoring
- Build risk management frameworks including VaR, stress testing, and scenario analysis.
- Monitor portfolio exposures, concentration risks, and factor loadings in real-time.
- Develop automated alerting systems for model degradation and performance anomalies.
- Support portfolio optimization and construction processes.
Technology & Automation
- Develop Python-based research and production systems with focus on scalability.
- Create automated model monitoring, reporting, and alert generation frameworks.
- Collaborate on technology infrastructure decisions and platform evaluations.
- Maintain code quality and documentation standards.
Qualifications
Professional Experience :
- 48 years of buy-side quantitative research in asset management, hedge funds, or proprietary trading.
- Proven track record in systematic investment strategy development and implementation.
- Experience with institutional-grade quantitative research and portfolio management.
Technical Proficiency
- Programming : Advanced Python (pandas, numpy, scipy, scikit-learn, quantitative libraries).
- Database : Hands-on Snowflake and SQL experience with large-scale data environments.
- Analytics : Statistical modeling, econometrics, and machine learning techniques.
- Platforms : Bloomberg Terminal, Refinitiv, or equivalent financial data systems.
Quantitative Expertise
- Deep understanding of factor models, portfolio optimization, and systematic risk management.
- Knowledge of derivatives pricing, fixed income analytics, and alternative investment structures.
- Experience with market microstructure analysis and high-frequency data processing.
- Familiarity with performance attribution methodologies and benchmark & Analysis :
- Strong problem-solving abilities with exceptional attention to detail.
- Ability to translate quantitative insights into actionable investment recommendations.
- Excellent presentation skills for communicating complex research to stakeholders.
- Collaborative approach to working in cross-functional investment teams.
Educational Background
- Master's degree in Finance, Economics, Mathematics, Statistics, Physics, or Engineering.
- CQF, CFA, FRM or equivalent professional certification preferred.
- Strong academic foundation with demonstrated quantitative aptitude.
Regulatory Awareness
- Understanding of SEBI AIF regulations and compliance frameworks.
- Knowledge of investment management risk controls and regulatory reporting requirements.
Preferred Skills
- Industry Recognition : Published quantitative research or contributions to investment thought leadership.
- Multi-Asset Expertise : Experience across equity, fixed income, commodities, and alternative investments.
- Innovation Mindset : Interest in machine learning, alternative data, and emerging quantitative techniques.
- Advanced Programming : Proficiency in additional languages such as R, C++, or Julia; experience with version control (Git) and code optimization techniques.
- Domain Specialization : Strong background in specific asset classes such as Indian equities & emerging markets.
- Entrepreneurial Drive : Self-motivated individual comfortable building scalable systems from ground-up in a growing AIF technology environment.
- Industry Certifications : Additional qualifications or specialized quantitative finance credentials will be a plus.
- Alternative Data & AI : Experience with NLP and AI techniques for extracting investment signals from alternative text data sources (such as Filings, Analyst Reports and Transcripts) and developing reasoning-based AI models for systematic decision-making will be a plus.
Pay range and compensation package :
Competitive with industry standards, including performance-based incentives.(ref:hirist.tech)
