Alpha Alternatives - Quant Researcher

Alpha Alternatives :

Alpha Alternatives is a multi-asset class alternatives asset management platform based out of India and Singapore, with over 22000 crores of assets under management, and deep focus on alpha generation.

We are passionate about finding alternative investment opportunities that can deliver superior risk-return characteristics. We operate across various alternative spaces like Equities, Commodities, Absolute Returns, Structured Credit, Fixed Income, Quant, and Infrastructure.

Our products span across various investment structures such as NBFC (ND-SI), AIF (Cat II & III), PMS, RIA and Gift City.

Our team consists of 200+ people who are vastly experienced across domestic and global hedge funds and financial institutions and have strong academic credentials at top universities.

We are strongly performance driven and look for people who share a similar DNA.

We are seeking an experienced Quant Researcher to join EQAR.

The ideal candidate will develop and implement statistical and machine learning models to identify and capitalize on trading opportunities.

Roles & Responsibilities :

- Research, design, and develop systematic trading strategies across equities, futures, or options, with a primary focus on Indias equity derivatives markets.

- Design and validate mid-frequency alpha signals leveraging order flow dynamics, volatility dislocations, term-structure skews, and statistical arbitrage opportunities.

- Conduct cross-sectional and time-series analysis on futures and options data to identify predictive patterns and inefficiencies.

- Build and maintain robust backtesting frameworks using high-frequency data, ensuring strategy resilience across diverse market regimes and incorporating realistic assumptions on slippage, transaction costs, and capital deployment.

- Engineer and optimize data pipelines for real-time and batch processing, handling large-scale tick and minute-level datasets for Indias F&O markets.

- Monitor and recalibrate live strategy performance, adjusting signals and model parameters in response to changing market conditions and microstructure shifts.

- Apply advanced statistical, econometric, and machine learning techniques for alpha generation, risk

modelling, and performance enhancement.

- Work closely with Portfolio Managers, technologists, and traders to implement research ideas into production, ensuring seamless integration of smart order routing, execution logic, and real-time risk controls.

- Participate actively in strategy review meetings, contributing to cross-strategy idea generation and fostering collaboration between research and technology teams.

- Stay informed on latest academic research, market developments, and technology trends to continually refine research methods and trading models.

Required Qualifications :

- Bachelors or Masters in mathematics, Statistics, Computer Science, Physics, Engineering, or related quantitative fields.

- 3+ years of experience in quantitative research or systematic trading.

- Strong knowledge of probability, statistics, time-series analysis, optimization, and machine learning.

- Proficient in programming languages such as Python, C++, or Java; familiarity with data analysis libraries.

- Experience with option pricing models, backtesting frameworks and handling large financial datasets (e.g., tick-level or intraday bar data).

- Understanding of market microstructure, transaction cost analysis, and execution slippage modelling.

Additional Skills (Good to have but not mandatory) :

- C++ proficiency.

- Prior experience at a prop desk, hedge fund, or institutional trading firm.

- Familiarity with broker APIs, OMS/EMS platforms, or building execution interfaces.

- Understanding of capital efficiency, collateral optimization, and portfolio margin frameworks.

If you are a talented individual with a sharp eye for detail, who can challenge the entire team, and would thrive in an innovative and entrepreneurial environment, apply for this exciting opportunity with Alpha Alternatives.

Location : Dadar, Mumbai.