Quantitative Research Analyst

PIMCO is a global leader in active fixed income with deep expertise across public and private markets. We invest our clients’ capital across a range of fixed income and credit opportunities, leveraging our decades of experience navigating complex debt markets. Our flexible capital base and deep relationships with issuers have helped us become one of the world’s largest providers of traditional and nontraditional solutions for companies that need financing and investors who seek strong risk-adjusted returns.

Since 1971, our people have shaped our organization through a high-performance inclusive culture, in which we celebrate diverse thinking. We invest in our people and strive to imprint our CORE values of Collaboration, Openness, Responsibility and Excellence. We believe each of us is here to help others succeed and this has led to PIMCO being recognized as an innovator, industry thought leader and trusted advisor to our clients.

JOB DESCRIPTION The commodities business is an important part of PIMCO’s investment platform. We are seeking a Quantitative Research Analyst / Desk Quant to join our front-office Commodities Analytics team in Newport Beach. The role will provide direct quantitative support to specialist Portfolio Managers trading listed and OTC derivatives across energy, power, agricultural, metals and soft commodity markets.

The successful candidate will combine rigorous statistical and econometric modelling skills with strong commodities knowledge and practical software-development capabilities. Working closely with Portfolio Managers, traders, quantitative researchers and technologists, the analyst will develop research, risk and pre-trade analytics used to identify relative-value opportunities, manage portfolios and support investment decisions. The role will also contribute to the expansion of analytics coverage across commodity markets and the continued development of the team’s technology and AI-enabled research capabilities.

RESPONSIBILITIES Develop quantitative tools and empirical studies to support relative-value analysis, trading-opportunity evaluation and portfolio-management decisions across commodity markets

Build, enhance and maintain models that generate risk analytics for existing and prospective commodity positions

Develop pre-trade analytics and research tools within the team’s Python ecosystem, with an emphasis on robust, scalable and reusable solutions

Provide timely quantitative support to Portfolio Managers and traders during US trading hours, including day-to-day risk management and operational analysis

Research, back-test and maintain systematic, option and quantitative investment strategies

Apply statistical, econometric and machine-learning techniques to commodity-specific datasets and investment problems

Contribute to the enhancement of PIMCO’s technology infrastructure supporting commodity and quantitative strategies

Help broaden analytics coverage across energy, power, metals, agriculture and soft commoditiesREQUIREMENTSMaster’s degree or PhD in mathematics, statistics, econometrics, financial economics, physics, engineering, computer science or another highly quantitative discipline;
PhD preferred2–5 years of relevant experience as a commodity quant supporting a sell-side trading desk or a quantitatively oriented asset manager; exceptional junior candidates with directly relevant doctoral research will also be considered

Strong grounding in probability, statistics, econometrics, financial mathematics and empirical research

Demonstrated experience modelling commodity-specific processes, ideally across one or more of power, weather, oil, natural gas, metals or agricultural markets

Strong statistical and econometric modelling skills; knowledge of risk-neutral derivatives modelling and option analytics is desirable

Advanced programming ability in Python with experience delivering reliable analytical or research tools

Experience developing risk analytics, systematic-strategy research, option-strategy back-tests or pre-trade analytics

Exposure to machine learning, AI engineering or modern data-science techniques is desirable

Ability to work closely with Portfolio Managers…