Quantitative Researcher-1

Experience: 3-5 years

Location: Flexible (Indore and Bangalore preferred)

Department: Research

Reports To: Client Portfolio Manager / CIO

Job Summary

We are seeking an experienced and highly analytical Quantitative Researcher to join a dynamic quantitative research team. Reporting directly to the Client CIO, the successful candidate will apply statistical and quantitative methods to analyze data, identify predictive signals, and meaningfully contribute to the development of systematic equity trading strategies. Strong Python programming skills and experience in working with medium-to-large financial datasets are essential.

Key Responsibilities

• Conduct rigorous quantitative analyses on financial data to identify predictive patterns and signals forecasting equity returns.
• Develop, test, and refine predictive models to generate robust trading signals.
• Collaborate closely with the CIO, research team, and trading team to translate quantitative insights into actionable trading strategies.
• Manage the full lifecycle of research projects, from hypothesis formulation through back-testing, validation, and live implementation.
• Continuously monitor model performance, adapting strategies as market conditions evolve.
• Enhance and maintain existing quantitative research infrastructure, tools, and data processing workflows.

Qualifications

• Bachelor’s degree in a quantitative discipline (Mathematics, Statistics, Physics, Computer Science, Electrical Engineering, or related fields) is required; a Master’s degree or Ph.D. in a quantitative discipline is strongly preferred.
• 3–5 years of direct experience in quantitative research or strategy development at a hedge fund, proprietary trading firm, or quantitative financial institution; prior experience specifically with equity markets and equity-oriented quantitative strategies is highly desirable.
• Demonstrated experience managing, cleaning, and analyzing medium to large datasets, including financial time-series and alternative datasets; familiarity with portfolio optimization techniques and risk modeling frameworks is beneficial.
• Solid foundation in statistical methods with practical experience applying statistical and machine learning techniques to financial data; experience integrating quantitative models into live trading environments is strongly preferred.
• Strong proficiency in Python programming, including libraries such as Pandas, NumPy, scikit-learn, and related data science tools.
• Exposure to distributed computing environments, databases, and cloud-based platforms for quantitative research is beneficial.
• Excellent analytical abilities, critical thinking skills, and meticulous attention to detail.

What We Offer

• Competitive salary with attractive performance-driven bonuses.
• Collaborative, intellectually stimulating, and entrepreneurial work environment.
• Direct mentorship and professional growth opportunities under experienced leadership.
• Access to robust infrastructure and comprehensive datasets for deep analytical exploration.