Data Scientist 1

The Southwest Center for Advancing Clinical and Translational Innovation (SW CACTI, also known as CTSC) at the UNM Health Sciences Center (HSC) is seeking an experienced, strategic, and effective Data Scientist 1 to provide scientific programming, translational informatics, and research DevSecOps support in complex research computing environment. Under general supervision and in close collaboration with a multidisciplinary data analyst team, the qualified candidate will help design, deploy, administer, and continuously improve the computing platforms, servers, containers, workflows, and security processes that support AI/ML, clinical and translational informatics, CFDE/OMOP-linked data resources, GPU/HPC systems, Kubernetes/CyVerse environments, and multi-institutional research collaboration.

Tasks include developing and maintaining databases and research software for advanced analytics; ensuring data integrity and secure storage; analyzing system performance; and designing and implementing complex data workflows and infrastructure-as-code deployments. Responsibilities also include clearly documenting workflows, testing them on simulated and real-world datasets, generating experimental results, and producing robust, distributable software packages using reproducible research practices, GitHub/GitHub Actions, Ansible, containerization, automated testing, and secure deployment practices where appropriate.

The position also involves working with and delivering presentations to a range of interdepartmental stakeholders to provide support to faculty, researchers, students, and other computational staff on the development of research computing platforms, AI/ML services, secure data enclaves, system management tools, architectural assessments, training-as-code resources, and translational informatics workflows. The ideal candidate will be a self-motivated individual who enjoys a diverse range of projects, has proven technical skills, and keeps up with advances in computer science and technology.

This position will help operationalize SW CACTI's Health Informatics aims by supporting cross-institutional infrastructure, secure data enclaves, AI/ML capabilities, CFDE/IDG/OMOP-enabled data integration, DevSecOps/MLOps practices, and reusable training and software resources for clinical and translational science.

The SW CACTI is a member of the national Clinical Translational Science Award (CTSA) consortium, funded by the National Institutes of Health (NIH). SW CACTI aims to remove barriers to translational science, accelerate clinical translational innovation, and advance health outcomes in the United States Southwest region. SW CACTI is a partnership between the University of New Mexico (UNM) and the University of Arizona (UA).

DUTIES AND RESPONSIBILITIES:

1. Provides scientific programming, systems administration, and research DevSecOps support for an advanced clinical and translational research computing environments, including Linux servers, GPU/HPC resources, containers, Kubernetes/CyVerse platforms, infrastructure-as-code, and AI/ML research workflows.

2. Provides support for monitoring system usage and health, ensuring operating systems are functioning at optimal performance and reliability levels, and working with institutional IT and security teams to support secure configuration, access control, vulnerability remediation, disaster recovery, and compliance for research systems.

3. Develops, documents, manages, and maintains research IT and DevSecOps processes, including server configuration, GitHub/GitHub Actions workflows, Ansible automation, container deployment, security review, backup, disaster recovery, and reproducible scientific workflow execution.

4. Works in collaboration with computational staff to manage hardware and software infrastructure to support a reliable, high-performance, and scalable computing environments for health informatics, secure data enclaves, AI/ML services, Common Fund Data Ecosystem (CFDE)/OMOP data integration, and multi-site clinical and translational research.

5. Participates in the configuration and tuning of batch queuing systems in high-performance, parallel computing production environments; collects and analyzes system utilization statistics and logs; identifies computer system anomalies and operational problems; and provides systems support for web applications, SSO and LDAP, name resolution, and cloud storage services as needed to support secure research computing, Kubernetes/CyVerse deployments, API-based microservices, AI/ML inference services, and large-scale research data workflows.

6. Engages in continuous professional development to remain at the cutting edge of research and best practices in health informatics, AI/ML, MLOps, DevSecOps, Linux systems administration, Kubernetes, CyVerse, CFDE resources, OMOP/OHDSI tools, secure data enclaves, and reproducible research method.

7. Provides technical support to SW CACTI, University Hospital IT, and HSC IT team members and serves as a bridge between research teams and enterprise IT/security teams to translate scientific requirements into secure, scalable, maintainable computing solutions while maintaining institutional compliance.

8. Tracks time and activities for ongoing projects to facilitate billing for services and to support project milestones, service metrics, dissemination, continuous quality improvement, and grant reporting.

9. Performs other duties and responsibilities as assigned.

Term Appointment; Funding available through 6/30/2027; Continuance beyond that date subject to availability of additional funding.

See the Position Description for additional information.

• Employees who provide services or work in patient care or clinical areas are required to be in compliance with the University's influenza vaccination requirement.

Bachelor's degree in a relevant field; at least 3 years of experience directly related to the duties and responsibilities specified.

Completed degree(s) from an accredited institution that are above the minimum education requirement may be substituted for experience on a year for year basis.

• Strong engineering background such as an undergraduate degree in engineering, and commitment to professional development in computer science or computer engineering such as a higher degree or degrees.
• Experience in data analytics approaches, methods, and tools, including interactive notebooks, web UIs, and Docker containerization, with emphasis on reproducible scientific workflows and deployment of analytic tools for clinical, translational, biomedical, or AI/ML research.
• Experience supporting data-intensive computing environments, including development of data and AI operating strategies, systems administration support, Linux server deployment and management, secure configuration, and machine learning workflows.
• Experience deploying and supporting AI/ML services, including large language models (LLMs), GPU-accelerated workloads, scalable inference systems, API-based microservices, model evaluation workflows, and secure shared research platforms in research or production environments.
• Proficiency in Python and commonly used libraries for AL/ML, data science, and agentic workflows.
• Experience with team-based software engineering practices, including version control using Git/GitHub and collaborative development workflows, GitHub Actions, issue tracking, code review, manual and automated testing, CI/CD, and deployment automation.
• Demonstrated experience administering Linux-based systems and high-performance computing (HPC) environments, including support for GPU-enabled computing and scalable computational workloads, secure server configuration, monitoring, backup, and interaction with enterprise IT/security teams.
• Experience with containerized and cloud-native computing environments, including Kubernetes, Docker, infrastructure-as-code, secure enclave architectures, and platforms such as CyVerse.
• Knowledge of relational database design, data modeling, and query development in SQL.
• Experience building and maintaining data pipelines and scalable workflows for large-scale research or clinical datasets, including EHR-derived data, OMOP/OHDSI data, biomedical knowledge graphs, CFDE resources, or molecular/clinical data integration.
• Strong foundation in applied mathematics and statistics, including multivariable calculus, linear algebra, probability, and statistical methods.
• Knowledge of data privacy, security, and regulatory compliance, including HIPAA and human research protections.
• Demonstrated ability to automate system administration, research software deployment, and machine learning workflows using DevOps, DevSecOps, infrastructure-as-code, Ansible, GitHub Actions, CI/CD, and/or MLOps practices.
• Security certification and/or experience implementing cybersecurity controls and cybersecurity standards within an enterprise or research computing environment, especially experience interfacing with IT security teams on secure research computing, HIPAA-regulated data, human-subjects data, controlled-access data, or multi-institutional data-sharing environments.
• Excellent written and oral communication skills, including the ability to deliver training, provide technical support, and produce high-level technical summaries.

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Positions posted with a Staff Type of Regular or Term are eligible for the Veteran Preference Program. See the Veteran Preference Program webpage for additional details.

The University of New Mexico is committed to hiring and retaining a diverse workforce. We are an Equal Opportunity Employer, making decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability, or any other protected class.

The University of New Mexico requires all regular staff positions successfully pass a pre-employment background check. This may include, but is not limited to, a criminal history background check, New Mexico Department of Health fingerprint screening, New Mexico Children, Youth, and Families Department fingerprint screening, verification of education credentials, and/or verification of prior employment. For more information about background checks, visit https://policy.unm.edu/university-policies/3000/3280.html. Refer to https://policy.unm.edu/university-policies/3000/3200.html for a definition of Regular Staff.