Design

The success of analytical projects has deeper roots than the mere complexity of the solutions or the quality of the data.

By refining the understanding of developers and consumers perspectives, their business, and data literacy along diverse motivations, a solution with greater odds of success can be designed and implemented.

I can help identify what to build and how along with hands on guidance on technical challenges associated with new or existing data science projects.

Education

Organizations should have the ownership of any critical intelligence stemming out of their data. Learning sessions are aimed at bringing autonomy to the client through the upskilling of their resources.

• Data preparation strategies
• Code versioning
• Data and models lifecycle management
• Model monitoring and explainability

• Introduction and enterprise usage
• Package development
• Performance optimization

Productivity

• Framework to achieve both flexible analytics adapted to emerging problems and the rigor and reproducibility required for making critical business decisions.

• Reporting automation
• Interactive data driven application and dashboards

• Adapt to multi-threaded operations
• Controlling allocations
• Translation to GPU / CUDA