Quant Developer & Researcher

Alpha Alternatives; Mumbai; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Alpha Alternatives in Mumbai is seeking a Quant Developer & Researcher to join our EQAR team. The ideal candidate will lead the development of systematic trading strategies and build research and execution infrastructure from ideation to production monitoring.

We value 5–10 years in quantitative research, strong skills in Python, C++, or Java, and hands‑on experience with backtesting, data pipelines, and live trading systems.

Qualifications

• Bachelor’s or Master’s in Mathematics, Statistics, CS, Physics, Engineering, or related quantitative fields.
• 5–10 years of experience in quantitative research, strategy development, or quant technology.
• Proficient in Python, C++, or Java; experience with backtesting and live data handling.

Responsibilities

• Research, design, and implement systematic trading strategies across equities, futures, and options, primarily in the Indian markets.
• Develop mid-frequency alpha signals using statistical, econometric, and machine learning techniques.
• Build and maintain backtesting frameworks using high-frequency and intraday data with realistic costs and slippage assumptions.
• Collaborate with traders, researchers, and portfolio managers to translate research ideas into production-ready strategies.

Skills

Python

C++

Java

Backtesting

Data pipelines

Education

Bachelor's or Master’s in a quantitative field

Job description

We are seeking a Quant Developer & Researcher to join our EQAR team. The ideal candidate will have 5-10 years of experience in quantitative strategy research and technology development – having worked on the full cycle from ideation and back testing to production deployment and performance monitoring.

You will play a pivotal role in leading the development of systematic trading strategies and in building the research and execution infrastructure to support them.

Quantitative Research & Strategy Development

• Research, design, and implement systematic trading strategies across equities, futures, and options, primarily in the Indian markets.
• Develop mid-frequency alpha signals using statistical, econometric, and machine learning techniques, leveraging order flow dynamics, volatility dislocations, and market microstructure patterns.
• Conduct cross-sectional and time-series analysis to identify and validate predictive signals.
• Build and maintain robust backtesting frameworks using high-frequency and intraday data, with realistic assumptions for transaction costs, slippage, and capital allocation.
• Continuously evaluate and recalibrate models to adapt to evolving market conditions.
• Design, develop, and maintain research platforms, trading infrastructure, and data pipelines to support large-scale quantitative research.
• Integrate market data feeds, broker APIs, and OMS/EMS platforms for real-time execution and risk management.
• Develop end-to-end software solutions — from data ingestion and model training to live monitoring dashboards and analytics.
• Implement efficient data handling and automation workflows using modern programming frameworks.
• Collaborate closely with traders, researchers, and portfolio managers to translate research ideas into production-ready strategies.
• Build a team of quants and developers.
• Participate in strategy review discussions, fostering cross-team collaboration and innovation.
• Stay abreast of the latest academic and industry research, and proactively contribute to the team’s methodological evolution.

Qualifications & Background:

• Bachelor’s or Master’s in Mathematics, Statistics, Computer Science, Physics, Engineering, or related quantitative fields.
• 3+ years of experience in quantitative research, strategy development, or quant technology – preferably at a prop desk, hedge fund, or institutional trading firm.
• Demonstrated experience in developing and deploying systematic trading strategies in live environments.
• Proficient in programming languages such as Python, C++, or Java; familiarity with data analysis libraries.
• Experience with option pricing models, back-testing frameworks and handling large financial datasets (e.g., tick-level, or intraday bar data).
• Understanding of market microstructure, transaction cost analysis, execution algorithms, and execution slippage modelling.
• Additional Skills (Good to have but not mandatory):
• 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.