Description

Description: 
• Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale and complexity 
• Develop novel machine learning (ML) algorithms and indicators for time-series forecasting prediction, with applications in actuarial reserving and the development of affordability programs 
• Implement state-of-the-art machine learning models and evaluate their performance 
• Communicate the performance of the machine learning algorithms across an interdisciplinary team
• Write both internal and external documentation of the novel algorithms, including publications in machine learning and other scientific conferences and journals 
• Develop our research and innovation agenda • Collaborate with the AI team and fellow scientists and engineers.

Education

Any Graduate