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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