Kivi Capital – Quantitative Researcher Role Kivi Capital

The Corporate Institute; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Mentorship program

Growth opportunities

Competitive compensation

Job summary

Kivi Capital in Gurgaon, India, seeks a Quantitative Researcher to research, develop, test, and improve quantitative trading strategies. You will work with portfolio managers and technologists to deploy strategies in production and continually boost performance.

Required are strong Python skills, a quantitative degree, and knowledge of statistics, time-series analysis, and backtesting frameworks. Experience with tick-level data or C++ is a plus.

Qualifications

• Bachelor’s degree in Mathematics, Statistics, Computer Science, Financial Engineering, or related quantitative field from a Tier-1 college/university.
• CGPA 8.5+; JEE Main/Advanced rank <1000 preferred.

Responsibilities

• Research and develop quantitative trading strategies using statistical and mathematical techniques.
• Backtest and simulate strategies using historical data.
• Identify alpha opportunities by analyzing market microstructure and order flow.
• Optimize models for profitability, execution efficiency, and risk-adjusted returns.
• Monitor live strategies and analyze deviations from expected performance.
• Collaborate with tech teams to implement strategies in production.

Skills

Python

NumPy/Pandas/SciPy

Time-series analysis

Mathematics/Statistics

Problem solving

Education

Bachelor’s degree in Mathematics/Statistics/CS/Financial Engineering

Tools

Backtesting frameworks

Tick-level data handling

C++

Job description

Quantitative Researcher

About Kivi Capital

Kivi Capital is a fast-growing Algorithmic Trading firm based in Gurgaon, India, specializing in quantitative trading strategies and their execution through advanced algorithmic trading infrastructure. Our mission is to leverage data, technology, and innovation to deliver superior risk-adjusted returns while maintaining robust risk management practices.

Role Overview

We are looking for a highly analytical and driven Quant Trader / Quant Researcher to join our trading team. In this role, you will be responsible for researching, developing, testing, and improving quantitative trading strategies across multiple market conditions. You will work closely with portfolio managers and technologists to deploy strategies in production and continuously enhance performance.

Key Responsibilities

– Research and develop quantitative trading strategies using statistical and mathematical techniques.

– Perform backtesting and simulation of trading strategies using historical market data.

– Identify alpha opportunities by analyzing market microstructure, price action, and order flow patterns.

– Optimize trading models to improve profitability, execution efficiency, and risk-adjusted returns.

– Conduct performance analysis and strategy attribution to identify strengths and weaknesses.

– Monitor live strategies and analyze deviations between expected and actual performance.

– Work with the technology team to implement strategies in production and improve execution logic.

– Ensure adherence to risk limits, internal compliance frameworks, and trading guidelines.

– Maintain detailed documentation of research methodology, strategy logic, and results.

Requirements

– Education: Bachelor’s degree in Mathematics, Statistics, Computer Science, Financial Engineering, or related quantitative field from a Tier-1 college/university.

– Academic Credentials: CGPA of 8.5 or above; strong performance in JEE Main & JEE Advanced / equivalent national exams. A rank below 1000 is preferred.

– Technical Skills: Strong proficiency in Python (NumPy, Pandas, SciPy, etc.).

– Strong understanding of probability, statistics, linear algebra, optimization, and time-series analysis.

– Experience with backtesting frameworks, strategy research, or market data analysis (internships/academic projects accepted).

– Strong problem-solving skills with a deep attention to detail.

– Ability to work in a fast-paced, performance-driven environment.

– Strong communication and collaboration skills.

Preferred Qualifications

– Exposure to trading strategies such as statistical arbitrage, mean reversion, momentum, market making, or volatility strategies.

– Knowledge of financial instruments (equities, futures, options).

– Familiarity with risk metrics such as Sharpe ratio, drawdown, volatility, and VaR.

– Experience working with tick-level data or high-frequency datasets.

– Knowledge of C++ is an added advantage.

What We Offer

– Opportunity to work on high-impact quantitative strategies with real capital deployment.

– Exposure to advanced trading infrastructure and execution systems.

– Merit-driven, intellectually challenging, and performance-focused culture.

– Competitive compensation with strong performance-linked incentives.

– Mentorship and rapid learning environment with strong growth potential.