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/GitHub.
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, NumPy, scikit-learn)
Streamlit or R Shiny for web application development
Git/GitHub 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 Secunderabad
🏢 Tiger Analytics
📍 Secunderabad