Senior Quantitative Model Developer

Job Description:

• The Quantitative Research Analyst role involves the development, implementation, and maintenance of sophisticated quantitative models that drive our alternative investment approach.
• Responsibilities include model development, data infrastructure management, strategy testing, risk management, and technology.

Key Responsibilities:

• 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.
• 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.
• 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.
• 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.
• 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.
• 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:

A competitive compensation package, including performance-based incentives, will be offered to the successful candidate.