AI Data Partner

Bridgewater Associates•New York, NY

2d•$200 - $400•Hybrid

About The Position

Data Partners are scrappy problem solvers who turn complex ideas about model evaluation and human judgment into production-grade data pipelines. Working side-by-side with senior investors, ML scientists, Data Leads, and technologists, you’ll construct and maintain the datasets, transformations, and metrics that power our LLM benchmark suites. This is a hands-on, high-impact role for someone who loves clean data, reproducible systems, and tight iteration loops — a mix of engineering craft and analytical curiosity.

Requirements

Strong ownership of data quality. Capable of precise and detailed review when necessary to complement systematic validations.
Communicates clearly, seeks context, and enjoys cross-functional collaboration.
3–5 years of experience in data analysis, data engineering, or ML ops roles.
Fluent in Python, Excel and SQL. Familiar with frontier LLMs and code assist tools.
4-year degree from an accredited undergraduate institution majoring in engineering, mathematics, statistics, or related field.

Nice To Haves

Experience with model evaluation or ML workflows a plus.
Bonus: familiarity with financial or macroeconomic datasets.

Responsibilities

Understanding: Start by understanding the business goals. Data Partners draw out expertise from the researcher or other SMEs to inform their approach.
Acquiring: Finding data and getting it into researchers’ hands. You will be capable of scraping websites, using APIs, and wrangling the data from how it exists externally to the structure needed by the project. Data Partners conduct data profiling and sanity checks to pull forward problems with quality and coverage.
Investigating: Data Partners investigate and analyze details of the data, based on previously known challenges and reacting to problems researchers uncover.
Improving: Data Partners improve and extend the dataset, applying logic to fix issues, pulling in more related data, longer history, or keeping it up to date as project evolves.
Hardening: Through time, you will harden the asset, e.g. make it more efficient to update, systemize validations to maintain quality through time, and standardize to make it easier to use with other data.
Developing: Apply techniques to standardize unstructured content to make it easier to find and use the most relevant content
Building: Benchmark data sets and use them to continually evaluate LLM systems.
Enable: Work with LLM system traces to enable diagnosability and process improvements.

Benefits

Health insurance with 100% premium covered and access to additional concierge medical services
401(k) plan with generous employer match
Paid time off, including fully paid parental leave and a competitive PTO package
Workplace flexibility and access to back up childcare
Financial assistance for family building support, including adoption and egg freezing
Workplace wellness, including on-site gyms, free meals and healthy snacks, and meditation rooms
An engaged and active community that includes many company events, affinity networks, and extracurricular interest groups

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