Commodities Quantitative Analyst - Global Commodities Index Products (GCIP)

Bank of America · London, United Kingdom

On-siteWorkplace
1w agoPosted · Aug 22
The MuseSource
$121kstatistician median
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Job Description

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.

Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates' physical, emotional, and financial wellness through affordable, competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Job Description

We are seeking a talented and driven Quantitative Analyst to join the Commodities team within the Quantitative Strategies and Data Group (QSDG), supporting the Global Commodities Index Products (GCIP) trading desk.

Commodity QSDG is a global team with members in London, New York, Houston, and Singapore. The team develops and supports quantitative platforms, analytical tools, models, and data solutions for commodities businesses across the Americas, EMEA, and APAC.

This London-based role will focus on the continued development of the strategic platform supporting Bank of America's commodities investible index franchise. The successful candidate will build scalable platform components, implement new indices and strategies, improve existing analytics and workflows, and support the platform in production.

The role is highly business-facing and involves close interaction with trading, index structuring, sales, and technology teams. It will suit someone who enjoys a fast-paced, high-intensity flow environment, values direct engagement with the business, and is comfortable balancing strategic platform development with timely support for trading priorities.

Responsibilities

Develop and maintain the Python platform supporting commodities investible indices

Implement new indices, strategies, as well as backtesting capabilities, and trading analytics

Build scalable data pipelines, calculation components, controls, and monitoring tools

Support the GCIP trading desk and resolve production, data, and calculation issues

Improve platform reliability, performance, testing, and maintainability

Work closely with trading, structuring, sales, and technology to deliver business priorities

What We Are Looking For

A strong degree in mathematics, statistics, computer science, engineering, physics, quantitative finance, or a related field

Strong Python programming and software development skills

Experience with structured development practices, including source control, testing, code review, and release processes

rRgorous problem-solving skills and strong attention to data quality and controls

An interest in building and owning production-quality quantitative platforms

Strong communication skills and the ability to work effectively in a business-facing, high-intensity environment

Preferred Skills

Experience with index, trading, risk, backtesting, or financial analytics platforms

Knowledge of SQL, kdb+/q, databases, APIs, or large-scale data processing

Understanding of investible indices, systematic strategies, or commodity derivatives

Knowledge of statistics, derivatives pricing, or financial engineering

Experience with production monitoring, reconciliation, and automated controls

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