Assistant Research Data Scientist -Data & Bioinformatics

Texas A&M University System • College Station, TX

1d

About The Position

About Texas A&M AgriLife
Texas A&M AgriLife is comprised of the following Texas A&M University System members:
Texas A&M AgriLife Extension Service
Texas A&M AgriLife Research
College of Agriculture and Life Sciences at Texas A&M University
Texas A&M Forest Service
Texas A&M Veterinary Medical Diagnostic Laboratory
As the nation’s largest most comprehensive agriculture program, Texas A&M AgriLife brings together a college and four state agencies focused on agriculture and life sciences within The Texas A&M University System. With over 5,000 employees and a presence in every county across the state, Texas A&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and make a difference in the world!

The Assistant Research Data Scientist – Data & Bioinformatics is a service-focused technical expert within the Center for Managed Technology Services (CMTS). This role supports researchers across disciplines by delivering outcome-based services in bioinformatics, data engineering, advanced analytics, and cloud-based research computing. Operating under CMTS’s cost-recovery service block model, the Assistant Research Data Scientist offers high-skill human capital that transforms raw data into reproducible workflows, actionable insights, and sustainable solutions. The successful candidate will work across multiple projects to analyze next-generation sequencing (NGS) data, design scalable pipelines, integrate heterogeneous datasets, and train researchers in modern data practices.

Position Structure
This is a full-time professional position reporting to the Director of CMTS. All work is scoped and delivered under a service model, enabling equitable access to high-skill expertise. The Assistant Research Scientist – Data & Bioinformatics may support multiple projects simultaneously and will focus on delivering reproducible, interpretable, and scalable results within each engagement.

Requirements

• Ph.D. with relevant experience in Bioinformatics, Data Science, Computational Biology, or related field.
• Hands-on expertise in NGS data analysis and/or large-scale data engineering.
• Proficiency in Python, R, SQL, and distributed computing frameworks (e.g., Apache Spark).
• Experience with workflow automation (Snakemake, Nextflow) and cloud platforms (Azure preferred).
• Strong interpersonal and communication skills.
• Service-oriented mindset with focus on measurable outcomes.
• Ability to multitask and work cooperatively with others.

Nice To Haves

• Significant experience in Bioinformatics, Data Science, Computational Biology, or related field.
• Experience with Azure Databricks, Delta Lake, or equivalent cloud-native analytics tools.
• Background in agricultural, life sciences, or environmental sciences.
• Familiarity with NIH/NSF data mandates, FAIR principles, and institutional compliance frameworks.
• Experience delivering technical training to non-technical audiences.

Responsibilities

• NGS and Bioinformatics Analysis Process raw sequencing data (quality control, alignment, assembly, variant calling).
• Apply functional annotation, gene expression analysis, and microbiome profiling.
• Deliver biological interpretations in formats suitable for publication, compliance, and grant deliverables.
• Scientific Leadership & Research Enablement Exercises independent scientific judgment and analysis to support and enhance research projects conducted by other researchers.
• Advises investigators on experimental design, analytical approaches, and appropriate computational methods across genomics, bioinformatics, and data science.
• Translates research questions into rigorous analytical strategies, selecting methods, models, and tools aligned with scientific objectives.
• Data Engineering and Cloud Analytics Build and optimize reproducible pipelines using Python, R, SQL, Bash, Snakemake, or Nextflow.
• Deploy workflows on HPC, institutional servers, and cloud platforms (Azure, AWS, Databricks).
• Implement FAIR-compliant data stewardship and governance.
• Applied Machine Learning and Statistics Apply statistical models, ML/AI methods, and predictive analytics to research datasets.
• Develop scalable analytic workflows for interdisciplinary projects across life sciences, agriculture, and environmental domains.
• Consultation and Researcher Engagement Translate PI research goals into executable data strategies.
• Recommend tools, platforms, and analytic approaches tailored to project needs.
• Support grant proposals through data strategy input and compliance alignment.
• Training and Education Deliver workshops, tutorials, and guides on bioinformatics, data science, and cloud workflows.
• Mentor graduate students and faculty in best practices for reproducibility and data management.
• Contribute to shared knowledge resources for institutional capacity-building.
• Performs other duties as assigned.

Benefits

• Health, dental, vision, life and long-term disability insurance with Texas A&M AgriLife contributing to employee health and basic life premiums
• 12-15 days of annual paid holidays
• Up to eight hours of paid sick leave and at least eight hours of paid vacation each month
• Automatic enrollment in the Teacher Retirement System of Texas
• Employee Wellness Initiative for Texas A&M AgriLife

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree