We developed a component to assess employees’ skills, compare persons based on their skill profiles, and identify skill gaps to derive actionable insights from them. The completed project allowed the customer to save around 10,000 man-hours and allowed for interactive engagement with their employees’ skill profiles.
The insurance company operating in a medical/health domain was facing the challenge of pricing policies development. For them, it was important to understand risks related to a particular patient and adjust pricing policy models accordingly. In turn, the customer was expecting to experience considerable savings.
We built an application based on a machine learning model to predict the probabilities of a particular disease according to many input features and parameters including medical history. For that, we trained a deep learning model that was effectively dealing with intrinsic challenges such as class im-balance. Additionally, we built a validation framework to objectively compare multiple approaches and ensure that the created model was significantly outperforming others.
The developed Data Science solution significantly outperformed the baseline models relying on statistics. The model outcome was used to optimize pricing policy to increase revenue and better manage risks.
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