Remote Microbiome Data Scientist - Transform Early-Life

Tiny Health; Austin (TX); À distance; USD 120 000 - 180 000; Plein temps

Résumé du poste

Tiny Health, a foundational microbiome startup, seeks a data scientist to advance early-life gut health research. You will analyze microbiome datasets, build biomarkers, and contribute to publications under the Head of Science, collaborating across product and research teams in a remote-first environment.

Preference for candidates with strong statistics, ML, and data visualization skills in R/Python, plus experience with longitudinal clinical data and large datasets.

Qualifications

• Master's or PhD in data science, computational biology, bioinformatics, systems biology, or microbiology.
• 3+ years full-time experience after Master’s or 0-1+ years with a PhD.

Responsabilités

• Analyze microbiome data (taxa abundances, diversity metrics, functional genes) to address research questions.
• Develop and maintain microbiome metrics and biomarkers using statistical and ML methods.
• Conduct statistical analyses of longitudinal clinical data.
• Prepare data visualizations, reports, and presentations for stakeholders and publications.
• Draft research protocols, analysis plans, and clinical study reports.
• Work independently across multiple projects in a fast-paced, collaborative environment.
• Support development of new product and study concepts.
• Contribute to scientific publications and proposals.

Connaissances

Statistics

Machine learning

Data visualization

R

Python

SQL

Longitudinal data

Communication

Formation

Master's or PhD in a relevant field

Outils

R

Python

SQL

Jupyter

Description du poste

Tiny Health, a foundational microbiome startup, seeks a data scientist to advance early-life gut health research. You will analyze microbiome datasets, build biomarkers, and contribute to publications under the Head of Science, collaborating across product and research teams in a remote-first environment.

Preference for candidates with strong statistics, ML, and data visualization skills in R/Python, plus experience with longitudinal clinical data and large datasets.