What You'll Do:

- Analyse and integrate clinical and multi-omics datasets (e.g., genomics, proteomics) to extract actionable insights.
- Develop and validate predictive models for biomedical research and biomarker discovery.
- Apply Design of Experiments (DOE) and statistical methods to support research objectives.
- Build interactive web applications using Streamlit or R Shiny for data visualization and exploration.
- Ensure reproducibility, code quality, and adherence to industrialized coding best practices using Git/Git Hub.
- Collaborate with cross-functional teams including bioinformaticians, data engineers, and clinicians.
- Document analysis workflows, methodologies, and results in a transparent and structured manner.
- Communicate findings through reports, dashboards,



and presentations to technical and non-technical stakeholders.

Technical Skills Programming & Tools:

- R (Tidyverse), Python (pandas, Num Py, scikit-learn)
- Streamlit or R Shiny for web application development
- Git/Git Hub for version control and code management
- GCP

What You Need:

- Data Science & Modeling:
- Exploratory Data Analysis (EDA), Statistical Modeling, Predictive Modeling
- Clinical data interpretation and Omics data integration
- Design of Experiments (DOE), Reproducibility & Repeatability
- Data visualization (ggplot2, matplotlib, seaborn, etc.)

📌 Data Scientist/Senior Data Scientist (India)
🏢 Tiger Analytics
📍 India