FDA NAMs-Aligned
We are redefining human-centric drug testing through the convergence of 3D bioprinting, microfluidics, and AI. As a Biomedical Data Analyst, you will transform complex experimental results from 3D bioprinting, organ-on-chip systems, and multimodal imaging into meaningful insights that guide discovery, validation, and decision-making across our human-centric drug testing platform.
Key Responsibilities
In this role, you will analyze large and diverse biomedical datasets to uncover patterns, correlations, and predictors of tissue performance and drug response. You’ll collaborate closely with biologists, engineers, and AI scientists to design robust data pipelines that ensure reliability, reproducibility, and regulatory readiness.
- Collect, curate, and preprocess datasets from imaging, microfluidic sensors, and bioprinting experiments.
- Perform exploratory data analysis (EDA) and build statistical models to identify trends in toxicity, efficacy, and biological performance metrics.
- Integrate multi-source datasets (phenotypic, omics, and material parameters) for advanced correlation and clustering studies.
- Collaborate with AI scientists to train and validate predictive models and evaluate algorithmic performance.
- Develop dashboards and visual analytics tools for internal reporting and cross-disciplinary collaboration.
- Apply bioinformatics or computational biology tools to link experimental outcomes with molecular mechanisms.
- Ensure compliance with data integrity, FAIR principles, and documentation standards for research reproducibility and IP generation.
Preferred Qualifications
We are seeking analysts who blend quantitative rigor with biological intuition—professionals who can translate complex datasets into actionable insights that advance human-relevant research.
- MSc or PhD in Bioinformatics, Computational Biology, Data Science, Biomedical Engineering, or related fields.
- Strong proficiency in Python or R, with experience using libraries such as NumPy, pandas, SciPy, scikit-learn, or tidyverse.
- Experience in statistical modeling, multivariate analysis, and data visualization (e.g., Plotly, Power BI, Tableau, or Matplotlib).
- Knowledge of biological datasets including transcriptomics, imaging, or high-throughput screening data.
- Understanding of experimental design, reproducibility, and quality control for wet-lab-generated data.
- Experience integrating data from multiple modalities or time-series experiments is highly desirable.
- Familiarity with cloud-based data workflows, version control, and collaborative analytics environments.
What We Value
Our foundation is built on the convergence of curiosity, ethics, and excellence. We believe that the future of healthcare innovation depends not just on the technologies we create, but on the values that guide how we create them.
01
Integrity
Every experiment is grounded in rigor, reproducibility, and transparency. We hold ourselves to the highest ethical standards in pursuit of human-relevant science.
02
Innovation
We thrive on asking “why not?” and explore the uncharted spaces where biology meets computation — transforming bold ideas into functional tissue systems.
03
Interdisciplinarity
We unite biology, engineering, and artificial intelligence—transforming cross-disciplinary insight into tangible breakthroughs.
04
Impact
Every printed tissue, every line of code, every experiment moves us closer to a world where drugs are tested safely, efficiently, and humanely — for the benefit of all.
Why Join Z24 Bio
Joining Z24 Bio means becoming part of a deep-tech movement that is transforming how the world discovers, tests, and delivers medicine. We’re not just building tissue models—we’re building the future of human-relevant science.
Every project you lead at Z24 Bio carries real-world impact—from bioprinted tissues that replace animal models to AI that predicts patient safety. Here, innovation isn’t confined to the lab—it drives ethical progress for humanity.
Global Collaboration
Work alongside scientists, engineers, and visionaries from top research institutions and technology hubs across the world.
