From raw data to decisions
We build the full analytics path: collection, cleaning, statistical testing, modelling and clear reporting. Every figure in a report can be regenerated from the code and data that produced it.
Capabilities
- Exploratory analysis and statistical hypothesis testing
- Regression, classification and clustering
- Time-series forecasting
- Interactive dashboards for non-technical stakeholders
- Data pipelines and quality checks
Tools we use
Python (NumPy, pandas, scikit-learn), R, SQL and modern visualisation libraries, with results delivered as notebooks, reports or live dashboards.
See how analytics supports our bioinformatics work.