Quantitative Developer – Backend & Real-Time Systems

GreyOak Capital Intelligence Pvt Ltd; Mumbai; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

GreyOak Capital Intelligence Pvt Ltd in Mumbai invites a Quantitative Developer to join the Quant Research team, translating research, strategy logic and forecasting models into robust production systems. This is a hands-on role covering quantitative research implementation, backtesting infrastructure, financial-market data, real-time systems and production engineering.

The ideal candidate should be comfortable understanding existing quantitative systems, improving their architecture and

Qualifications

• 3-5 years of relevant experience in Quantitative Development, Algorithmic Trading, Systematic Trading, Trading Infrastructure or financial-market technology.
• Strong hands-on programming experience in Python.
• Strong SQL and experience working with large datasets.
• Strong working knowledge of NumPy, Pandas and/or Polars.
• Experience developing backtesting, strategy, signal-generation or quantitative analytics systems.
• Strong understanding of financial time-series and market data.

Responsibilities

• Develop and productionise quantitative research, strategies, models and market-intelligence systems.
• Build and maintain multi-stock and multi-timeframe backtesting and simulation infrastructure.
• Develop scalable systems for processing historical and real-time financial-market data.
• Build strategy, classification, forecasting and quantitative analytics engines across large security universes.
• Ensure point-in-time correctness and prevent look-ahead bias, data leakage, timestamp misalignment and other backtesting errors.
• Optimise Python workloads for speed, memory efficiency and scalability.
• Build and maintain REST APIs, WebSocket services and backend systems for delivering quantitative outputs.
• Work with PostgreSQL, Redis and large financial datasets.
• Handle real-time market-data feeds, connection reliability, missing data, retries and recovery mechanisms.
• Conduct walk-forward, out-of-sample and robustness testing of quantitative systems.
• Debug, monitor and resolve production issues across quantitative and market-data systems.
• Work closely with Quant Researchers to translate research code and notebooks into modular, maintainable production systems.
• Improve existing system architecture to support increasing numbers of securities, strategies, models and timeframes.
• Take end-to-end ownership of quantitative systems from research implementation to production deployment and monitoring.

Skills

Python

SQL

NumPy

Pandas

Polars

Backtesting

REST APIs

WebSockets

PostgreSQL

Redis

Docker

Git

Tools

FastAPI

Docker

Linux

Redis

PostgreSQL

AWS

Job description

GreyOak Capital Intelligence is an early-stage financial-market intelligence company building proprietary quantitative systems for traders, investors and financial institutions.

We are looking for a Quantitative Developer who can work closely with our Quant Research team to convert quantitative research, strategy logic and forecasting models into reliable, scalable production systems.

This is a hands-on role covering quantitative research implementation, backtesting infrastructure, financial-market data, real-time systems and production engineering. The ideal candidate should be comfortable understanding existing quantitative systems, improving their architecture and performance, and taking ownership from research implementation through production deployment.

Job Responsibilities

• Develop and productionise quantitative research, strategies, models and market-intelligence systems.
• Build and maintain multi-stock and multi-timeframe backtesting and simulation infrastructure.
• Develop scalable systems for processing historical and real-time financial-market data.
• Build strategy, classification, forecasting and quantitative analytics engines across large security universes.
• Ensure point-in-time correctness and prevent look-ahead bias, data leakage, timestamp misalignment and other backtesting errors.
• Optimise Python workloads for speed, memory efficiency and scalability.
• Build and maintain REST APIs, WebSocket services and backend systems for delivering quantitative outputs.
• Work with PostgreSQL, Redis and large financial datasets.
• Handle real-time market-data feeds, connection reliability, missing data, retries and recovery mechanisms.
• Conduct walk-forward, out-of-sample and robustness testing of quantitative systems.
• Debug, monitor and resolve production issues across quantitative and market-data systems.
• Work closely with Quant Researchers to translate research code and notebooks into modular, maintainable production systems.
• Improve existing system architecture to support increasing numbers of securities, strategies, models and timeframes.
• Take end-to-end ownership of quantitative systems from research implementation to production deployment and monitoring.

Required Qualifications, Capabilities, And Skills

• 3-5 years of relevant experience in Quantitative Development, Algorithmic Trading, Systematic Trading, Trading Infrastructure or financial-market technology.
• Strong hands-on programming experience in Python.
• Strong SQL and experience working with large datasets.
• Strong working knowledge of NumPy, Pandas and/or Polars.
• Experience developing backtesting, strategy, signal-generation or quantitative analytics systems.
• Strong understanding of financial time-series and market data.
• Understanding of look-ahead bias, data leakage, survivorship bias, overfitting and point-in-time testing.
• Experience building and consuming REST APIs and WebSockets.
• Experience with PostgreSQL and Redis.
• Experience handling historical and real-time market-data pipelines.
• Strong debugging, problem-solving and performance-optimisation skills.
• Working knowledge of Git, Linux and Docker.
• Ability to understand an existing quantitative codebase and independently improve its performance, architecture and reliability.
• Hands-on experience taking systems from development or research environments into production.

Preferred Qualifications, Capabilities, And Skills

• Experience working with NSE, BSE, equities, futures or options market data.
• Experience integrating broker APIs or real-time market-data feeds.
• Experience with FastAPI or similar Python backend frameworks.
• Experience with AWS, DigitalOcean, GCP or similar cloud infrastructure.
• Experience with multiprocessing, Numba, Cython, C++ or other Python performance-optimisation techniques.
• Understanding of trading-system metrics including returns, drawdown, win rate, expectancy, Sharpe ratio and related performance measures.
• Previous experience at a proprietary trading firm, broker, quantitative fintech, systematic trading company or market-data business.
• Experience building systems that operate across hundreds of securities, multiple strategies and multiple timeframes.
• Strong analytical and problem-solving skills with the ability to independently own complex quantitative engineering problems.

Important

This role is focused specifically on quantitative and trading-system development. Candidates whose experience is primarily in general full-stack development, dashboard development, business intelligence or data-analysis reporting without hands-on quantitative or financial-market systems experience may not be suitable.

Applicants should be prepared to discuss one quantitative, trading, backtesting or market-data system they have personally built or significantly contributed to, including the architecture, scale and their individual contribution.