Principal Data Scientist

University of Colorado•Aurora, CO

1d•Hybrid

About The Position

This full-time Data Scientist position in the laboratory of Dr. Aaron Michels will play a key role in advancing translational research focused on immune-mediated diseases by designing, implementing, and maintaining robust data analytics pipelines. This position is responsible for managing and integrating complex clinical, immunologic, genomic, and laboratory datasets; applying advanced statistical, machine learning, and computational methods to uncover meaningful biological insights. The Data Scientist will also contribute to study design, data quality control, visualization, and reproducible reporting of results. Strong communication skills are essential, as the role involves translating analytical findings into clear, actionable results for manuscripts, grants, and scientific presentations. The Barbara Davis Center for Diabetes (BDC) specializes in type 1 diabetes research and care for children and adults. Clinicians, clinical researchers, and basic biomedical scientists collaborate at the BDC to find the most effective treatment, prevention, and cure for type 1 diabetes. The Michels Laboratory (www.michelslab.com) is a nationally recognized, NIH‑funded research program focused on uncovering the immune‑mediated mechanisms driving type 1 diabetes. With over 15 years of continuous NIH support, the laboratory has assembled uniquely rich, longitudinal datasets from individuals at risk for type 1 diabetes, newly diagnosed patients, and well‑matched controls. These datasets span demographics, genetics, autoantibody profiles, and T cell receptor sequencing. A central goal of the lab is to leverage these data to understand and predict disease progression across stages of type 1 diabetes, offering a rare opportunity to conduct impactful, data‑intensive translational research with direct relevance to human disease.

Requirements

Bachelor’s degree in Bioinformatics, Biostatistics, Biology, Chemistry, Genetics, Computational Biology, Data Science, Computer Science or related field
Three (3) years of professional level research and bioinformatic analyses experience
Applicants must meet minimum qualifications at the time of hire.
Knowledge of translational biomedical research, including immunology, autoimmunity, and type 1 diabetes, with experience analyzing clinical and laboratory data.
Strong skills in statistical analysis, bioinformatics, and machine learning applied to high‑dimensional biomedical datasets (e.g., clinical, genomic, immunologic, and T cell receptor sequencing data).
Proficiency in building and maintaining scalable, reproducible data pipelines using modern data science tools (e.g., R, Python, SQL).
Ability to ensure data quality, integrity, documentation, and reproducibility, and to create clear visualizations and analytical reports.
Strong communication and collaboration skills, with experience contributing to manuscripts, grants, and multidisciplinary research teams.

Nice To Haves

Master’s degree in Bioinformatics, Biostatistics, Computational Biology, Data Science, Computer Science or related field
Four (4) years of experience analyzing data using high-performance computing

Responsibilities

Develop, implement, and maintain scalable data pipelines for clinical, immunologic, genomic, and laboratory datasets generated in Dr. Aaron Michels’ laboratory.
Apply advanced statistical, bioinformatics, and machine learning methods to analyze high-dimensional biomedical data such as T cell receptor sequences and address research questions related to type 1 diabetes.
Collaborate closely with clinicians, laboratory scientists, and investigators to support study design, data interpretation, and hypothesis generation.
Ensure data integrity, quality control, documentation, and reproducibility of analyses.
Create clear visualizations, dashboards, and summary reports to communicate findings to diverse scientific and clinical audiences.
Contribute to manuscripts, grant applications, and scientific presentations by providing analytical expertise and data-driven insights.