The Argonne Leadership Computing Facility (ALCF) is actively seeking a Scientific Data Engineer with a specialized focus on promoting the FAIR (Findable, Accessible, Interoperable, Reusable) principles in data management. This role is crucial in organizing, managing, and preparing research data for use beyond the immediate research teams, encompassing external researchers and AI/ML model development.

The Scientific Data Engineer will play a pivotal role in ensuring that the data curated and maintained at our facility adheres to the highest standards of accessibility and reusability. This position is not only about maintaining data integrity and organization, but also about enhancing the data’s value by making it easily findable and interoperable for varied external applications, including but not limited to AI training and collaborative research endeavors.

Key Responsibilities:

• Manage and curate a diverse range of data, ensuring it is not only well-organized for internal use but also prepared and formatted for external research collaborations and AI training purposes.
• Develop and implement data policies and practices that facilitate external access and usage, adhering to legal and ethical guidelines for data sharing.
• Collaborate closely with AI researchers to understand and fulfill data requirements for machine learning model training and validation.
• Establish robust data curation protocols that enhance the usability of data sets in various AI and machine learning contexts.
• Work with interdisciplinary teams to understand and anticipate the data needs of external researchers, ensuring that data is accessible, interoperable, and reusable across various domains.

Position Requirements

• Degree in Information Management, Computer Science, Data Science, or a related field.
• Experience in managing large scientific data collections, with a focus on preparing data for external use and AI training.
• Knowledge and experience with FAIR (Findable, Accessible, Interoperable, Reusable) principles in data management.
• Effective collaboration skills to work with interdisciplinary teams.
• Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork.

This position can be hired at one of two levels; the selected candidate will be placed at the appropriate level (RD2 - RD3) dependent upon the depth and breadth of relevant knowledge and skills. The minimum requirements for the two levels are as follows:

• RD2: Bachelors and 5+ years of experience, Masters and 3+ years, or PhD and 0+ years, or equivalent
• RD3: Bachelors and 8+ years of experience, Masters and 5+ years, PhD and 4+ years, or equivalent

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