Senior Research Data Support Analyst, YSE

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Serve as a senior technical resource for data‑intensive research across the Yale School of the Environment. Lead the design and deployment of scalable data systems, software tools, and computational workflows with consultative support to faculty and research groups. Act as liaison between researchers and university technical organizations providing storage, compute, cloud, and AI services.

Yale is developing a rich computational research support environment. The successful candidate will collaborate with other data and computational research support professionals across campus, including but not limited to the Yale Center for Research Computing (YCRC), the library and statistics lab, Data Intensive Social Science Center (DISSC), the Geospatial Data Research Center, and the Digital Humanities Lab. There are also opportunities to interact with Yale’s world‑class computer science and statistics and data science faculty and students.

The successful candidate will have strong software engineering fundamentals in Python; working proficiency in at least one of R or SQL; experience designing and deploying data pipelines and computational workflows in research environments; experience with Linux operating systems, HPC, job scheduling, and distributed computing; experience with machine learning & AI model development, evaluation, optimization, and deployment; experience with cloud platforms (e.g., AWS, Azure, Google Cloud);

experience managing large‑scale datasets, including out‑of‑core processing and columnar formats (Parquet, Arrow); proficiency with version control (Git/Git Hub) and collaborative development workflows; familiarity with containerization (Docker, Apptainer) and reproducible research environments. Experience working with a wide range of backgrounds and approaches.

This position offers the opportunity to address important environmental and sustainable challenges and make a positive impact on the world. This position will report to the senior associate dean or assistant dean for research at the Yale School of Environment.

Design, build, and maintain scalable data pipelines, computational workflows, and AI/ML systems that support faculty, post‑doc, and PhD student research. Consult with faculty and their post‑docs and graduate students on project scope, data architecture, and computational strategies. Discuss technical and university requirements and recommend approaches. Develop and deploy AI/ML models and tools such as LLM agents, computer vision pipelines, and predictive/forecasting systems aligned with environmental science and sustainability.

Implement statistical methods for descriptive and causal designs and learn new research methods as needed. Work with procurement and legal teams to assist researchers to locate and acquire more complex data resources. Serve as a resource to the university on improving these processes as needs arise. Serve as a mentor and a resource. May perform other duties as assigned.

• Demonstrated strong software engineering fundamentals in Python; working proficiency in at least one of R or SQL. Experience designing and deploying data pipelines and computational workflows in research environments.
• Ability to clearly communicate and document workflow.
• Ability to work on multiple unrelated projects simultaneously.
• Demonstrated interest in the environment, natural resources, or sustainable development.
• Ability to lead teams and workflows and ability to mentor others.

Master’s Degree in computer science, data engineering, statistics or related field and minimum 4 year’s experience.

• Consult to faculty and researchers regarding their projects and needed data infrastructure and processes. Discuss suggested project designs solutions and develop…