Quantitative Analyst
2 days ago
Job Title: Quantitative Analyst Trading Support (Equity Research)
Industry / Functional Area: Analytics / KPO / Research (or BFSI if you prefer finance-first)
Department / Role: Equity Research Analyst / Quantitative Analyst
Base Location: Mumbai, India (Remote option; must reside full-time in India)
Compensation: 15–20 LPA (~$15/hour)
Employment Type: Full-time
Job Description
We are a U.S.-based family office expanding our quantitative research capabilities in India. We are seeking two Quantitative Analysts to support our active trading strategies. The ideal candidate will combine a strong academic background in mathematics/statistics with hands-on programming skills and an interest in financial markets.
Key Responsibilities
- Research, test, and validate systematic trading strategies
- Clean, process, and analyze financial and alternative datasets
- Build and refine statistical models for signal generation and risk management
- Support backtesting, portfolio construction, and performance attribution
- Collaborate directly with senior leadership to translate research into live strategies
Required Qualifications
- Master's degree (M.A./M.Sc./M.Tech/MBA) in Mathematics, Statistics, Economics, Computer Science, Engineering, or another quantitative discipline
- Strong programming skills in Python (R or C++ also valuable)
- Solid knowledge of probability, statistics, linear algebra, and time-series analysis
- Ability to work independently and remotely with reliability and accountability
- Must be a full-time resident of India
Preferred Qualifications
- Exposure to financial markets, equity research, or algorithmic trading
- Familiarity with SQL, Pandas, NumPy, scikit-learn, or other data science tools
- Understanding of trading systems and execution models
- Experience with backtesting frameworks or financial data APIs
What We Offer
- Competitive compensation at 15–20 LPA
- Exposure to real-world trading operations and global markets
- Direct mentorship from senior leadership
- Flexible, remote-friendly work environment
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