Niklas Fürderer

Senior consultant within the data domain - varying projects and clients.

Grace Health was founded on the insight that for a majority of the worlds’ women, access to basic health services, reliable information and essential products is simply too inaccessible and stigmatised. Meanwhile, 1.9 billion women in emerging markets own their own phones and THAT is what we like to call opportunity! They are on a mission to improve health for all women, worldwide and are pioneering the health sector by being the leading female health platform designed for the next billion users. Niklas was part of the data team and due to a lack of resources became the sole data person for the whole organisation. His work included core feature maintenance and development (predictive algorithms with historic user health data). On the other hand, Niklas was the adopted the gateway role to allow different stakeholders accessing existing data sources. Besides, his work included data modelling, feature testing and performance evaluation, dashboard creations as well as data cleaning and insights generations. The working environment was split between GCP, AWS and local developments.

Nectarine Health™ at Home remote care system is built for life-loving independence, giving seniors the confidence to live at home more fully, every day, without having to compromise on their privacy or dignity, safe in the knowledge that help is always at hand. Niklas was part of the AI/ML team and contributed in various ways over a project duration of over 4 years. The aim was to generate and implement ML-based algorithms for everyday use which were based on continuous data streams of several sensors gathered by a singled wristband from individuals. The main and core functionalities included automated fall detection, out of bed detection, activities of daily living (ADL) detection, sleep analysis, and automated and continuous pattern analysis on a per-user basis. This goal was achieved by the following sub-projects: - Sensor data gathering, cleaning, and management - Data analysis and interpretation - Machine learning algorithm development, testing, and evaluating - Real-time testing with continuous sensor input streaming - Algorithm research and end-to-end testing