Commodities Research Associate

Bridgewater Associates LP•New York, NY

1h•$150,000 - $200,000•Hybrid

About The Position

This role sits in our Asia Strategies department, whose goal is to continue our growth down the journey of being the premier investment management firm in Asia. This entails developing great investment strategies reflecting our expertise, generating alpha in the markets, researching and publishing our understanding of the macroeconomic environment, and designing solutions to help our clients invest across the region. Within Asia Strategies, Asia Commodities is a dedicated investment team responsible for generating alpha and managing risk. The team's research and signals feed directly into the commodities strategy for Bridgewater's largest funds in the region, including the Asia Total Return Fund, China Total Return Portfolio, and Pan-Asia Total Return Fund. We're seeking a Data Engineer to join the Commodities team within Asia Strategies, embedded directly on the desk with direct impact on trading strategies and exposure to the CIO and Senior PMs responsible for key Asia strategies. You'll work in a tight-knit, fast-paced environment where the pipelines and data you own feed directly into live investment decisions. This position emphasizes (1) direct ownership of vendor data relationships and quality, (2) research-adjacent problem solving — understanding why the team needs the data concepts before you analyze it, (3) data operations spanning the full research cycle, from raw vendor feed to modeled data to live dashboards and trading indicators, and (4) sitting inside the investment process and developing expertise in Asia Commodities as an asset class. Given the size of the team, you'll drive your own agenda rather than wait to be told what's next — spotting a gap before it's flagged, pushing through a fix rather than escalating and waiting. We're looking for someone entrepreneurial and resourceful, who wants to build serious infrastructure while staying close to a live book and the decisions it drives.

Requirements

2–4 years of experience in a data engineering, data science, or analyst role at a commodity trading house, hedge fund, or research organization with exposure to commodities markets.
Familiarity with metals fundamentals and commodities market data preferred. Additional experience with other commodities (e.g. Ags, PetChem) would be a plus.
Experience with systematic commodities trading strongly preferred.
Strong programming skills in Python and SQL preferred. Experience writing production-quality, maintainable code
Experience working with modern data platforms (e.g. Snowflake or similar cloud data warehouses)
Willingness to expand toolkit to adapt to our scala based production stack
Strong desire to work with new development assistant technologies to drive productivity
Experience designing, documenting, and scaling commodities data and trading systems
Solid foundation in statistics, particularly time-series and cross-sectional analysis
Mandarin proficiency strongly preferred
Humility, innate curiosity, and openness to new ideas and approaches.
Driven, confident, and goal-oriented.
Honest, exceptionally direct, and eager to provide and receive objective feedback.
Constantly strive for self-improvement through feedback and self-reflection and are committed to the pursuit of excellence.

Nice To Haves

Additional experience with other commodities (e.g. Ags, PetChem) would be a plus.
Mandarin proficiency strongly preferred.

Responsibilities

Source and maintain vendor data feeds, working directly with vendors to resolve data quality issues and communicate new features
Transform granular, contract-level market data into derived analytical constructs — curves, spreads, aggregated indicators — that feed directly into research and portfolio decisions
Build the data infrastructure that feeds fundamental supply/demand balance models — from raw inventory, production, and shipment data to balance-ready inputs
Build and maintain dashboards and monitoring tools the team relies on daily — tracking both data health and market conditions, and flagging breaks or shifts before they affect the book
Partner closely with investors and developers to ensure data is research-ready, well-documented, and reproducible across simulation and live environments
Design, build, and maintain robust, scalable data pipelines supporting systematic commodities strategies.
Interrogate datasets to understand distributions, coverage gaps, stability over time, and structural breaks
Design and maintain our data ontology and schemas
Work across a variety of datasets ranging from traditional datasets to large alternative datasets
Work with shared data engineering and platform teams to evolve the broader data ecosystem while maintain team-level ownership and agility
Contribute to improvements in tooling, standards, and best practices that increase research velocity and system reliability
Partner with our investors to research questions on commodity markets and commodity-producing companies, with a specific focus on Asia and Chinese commodities markets, and turn that understanding into systematic trading strategies
Contribute fundamental context to data decisions – flagging when a data quality issue or vendor discrepancy has a market explanation worth surfacing to the research team
Incorporate AI/ML technologies into the team's research and data infrastructure