Quantitative Developer - Commodities

Millennium; Bengaluru; On-site; INR 1,200,000 - 1,500,000; Full time

Job summary

Millennium in Bengaluru is seeking an entry-level Quant Developer/Data Scientist to join the Quant Technology team. You will work on building analytics and tools for pre-trade research, focusing on commodities, data pipelines and modeling frameworks.

The role requires hands-on experience with Python, SQL and data analysis, and familiarity with Airflow, Flask and React. Collaboration with researchers and technology teams is essential in a fast-paced environment.

Qualifications

• Strong Python fundamentals for data science.
• SQL and database development experience.
• Experience with data pipeline lifecycle including access and modeling.
• Hands-on SDLC experience with development tools.
• Familiarity with Airflow, Flask and React.

Responsibilities

• Partner with researchers and developers to build analytics tools for commodities.
• Develop scalable data analysis and visualization tools for pre-trade research.
• Build end-to-end data pipelines across large commodity datasets.
• Contribute to in-house modeling frameworks and analytics libraries.
• Apply software development best practices across the full lifecycle.

Skills

Python

SQL

Data pipelines

Airflow

Flask

React

Tools

Git

Job description

About Millennium

Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

About Millennium

Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.

Meet the Team

The Quant Technology team sits within the Fixed Income & Commodities Technology group in Millennium’s Information Technology organization. The team develops and maintains in-house fundamental modeling frameworks, analytics tools, and infrastructure that support commodities trading. Working in a dynamic, fast-paced engineering environment, the team builds data-driven technology and trader-support capabilities for the business.

What You'll Do

• Partner with Quant Researchers, Portfolio Managers, and Technology teams to build fundamental commodities analytics and tools from the ground up.
• Develop scalable tools that support data analysis and visualization for pre-trade fundamental research.
• Build and maintain end-to-end data pipelines spanning diverse, large-scale commodities datasets.
• Contribute to in-house modeling frameworks, analytics libraries, and data tools that support the commodities business.
• Apply sound software development practices across the full development lifecycle, from data access and transformation through deployment and maintenance.

What You Bring

• Early-career experience, with up to 4 years of relevant professional experience preferred.
• Strong Python fundamentals for data science, along with SQL and database development experience.
• Experience across the data pipeline lifecycle, including data access, transformation, modeling libraries, and data analysis tools.
• Ability to work independently with hands-on experience across the full software development lifecycle and relevant development tools.
• Familiarity with agentic tools is highly preferred.
• Prior experience as a Quantitative Developer or Data Scientist within the financial industry is highly preferred.
• Commodities knowledge and hands-on statistical or data modeling experience are highly preferred.
• Familiarity with technologies and libraries such as Airflow, Flask, and React is highly preferred.