Methodology
We place great importance on choosing appropriate statistical methods for your analysis. We take into consideration factors such as the need for predictive accuracy, transparency of the model, and computing time. We employ software engineering best practices like version control and test-driven development to ensure the quality of our analytics.
- Powerful statistical models
- Efficient software implementations
- Insights for better decisions
We are experts in predictive analytics, working across the entire data lifecycle: acquisition, architecture, and analysis. We help clients identify the data most relevant to their business, develop systems for accessing it, and perform analyses.
Features
We apply state of the art statistical and machine learning algorithms to solve problems like:
- Predicting patient outcomes
- Detecting anomalous transactions
- Estimating the future returns from a stock trading strategy
- Computing on data too large to fit in memory
- Creating effective visualizations for complex data
