Scientific Data Engineer

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.

As a Scientific Data Engineer at ALCF, you will be responsible for developing and implementing data management strategies that align with the FAIR principles. This includes creating systems and protocols to improve the discoverability of data, ensuring data accessibility both within and outside the organization, and facilitating the interoperability and reusability of data sets for diverse scientific inquiries and AI-driven innovations.

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

Job Family

Research Development (RD)

Job Profile

Computational Science 2

Worker Type

Regular

Time Type

Full time

As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.  

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