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Ishmael Salifu

Lead Sr. Big Data Modeler/Architect at Medtronic

Ishmael Salifu is a solution-driven analytics professional with a strong background in designing and developing solutions in the healthcare sector, particularly in the realm of Big Data Analytics. Ishmael has a wealth of experience in conducting exploratory, descriptive, and predictive analysis utilizing statistical tools such as R and PySpark. Additionally, he excels in performing high-level log analytics and creating near real-time dashboards on NoSQL databases. Currently, he is involved in the design and development of an automated data processing pipeline that consumes Kafka payload and integrates it into a NoSQL database (HBASE).

In his career, Ishmael has developed predictive models using tools like Skytree and Rapid Miner to forecast outliers in medical claims and predict patient readmission rates. His primary interest lies in crafting algorithms and predictive models for analyzing sensor data from diverse sources such as high-powered grid stations, smart meters, smart appliances, medical devices, among others. His educational background includes studying Engineering at Ccny School Of Education, acquiring a Master of Science in Data Science from the University of St. Thomas, pursuing an Associates in Engineering at Normandale Community College, and obtaining a Bachelor of Science in Electrical Engineering specializing in Electronics Engineering from the University of Minnesota.

Ishmael Salifu has held significant roles in various organizations. He currently serves as the Lead Senior Big Data Modeler and Architect at Medtronic. Previously, he worked as a Digital Data Consultant specializing in Big Data Analytics at Accenture, a member of the Data Analytics team at UnitedHealth Group, a Software Engineer at Tata Consultancy Services, a Product Development and Testing Intern at Awear Technologies, and a Research Assistant at the School of Physical and Astronomy at the University of Minnesota.

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Location

Greater Minneapolis-St. Paul Area