Research engineers possess a comprehensive skill set that bridges both domains of data science and software engineering, making them uniquely qualified for their role.

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Additionally, incorporating human judgment and expertise into the decision-making process can act as a safeguard against potential biases or limitations of AI algorithms

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With their unique blend of expertise in both data science and software engineering, research engineers take on the end-to-end responsibility for developing and deploying data products or machine learning models.

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Augmented intelligence, the fusion of human expertise with AI recommendations, offers a promising approach to achieve optimal results in decision making.

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The optimal approach lies in harnessing the power of AI alongside human expertise — a concept we will explore further in subsequent chapters as we delve into augmented intelligence and ways to address cognitive biases for better decision outcomes.

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