Tijesunimi (Tj) Fatunmbi
About Tijesunimi (Tj) Fatunmbi
Tijesunimi (Tj) Fatunmbi is a Data Engineer specializing in analytics, currently employed at Health Catalyst. He holds a Bachelor's degree in Mathematics from the University of Ilorin and a Master's degree in Computer Science from Austin Peay State University.
Work at Health Catalyst
Tijesunimi Fatunmbi has been employed at Health Catalyst as a Data Engineer (Analytics) since 2021. In this role, he focuses on leveraging data to provide insights that support healthcare organizations in improving their operations and patient outcomes. His responsibilities include developing analytical solutions and methodologies to address complex challenges within the healthcare sector.
Education and Expertise
Tijesunimi Fatunmbi holds a Bachelor's degree in Mathematics from the University of Ilorin, where he studied from 2013 to 2017. He furthered his education at Austin Peay State University, earning a Master of Science in Computer Science from 2019 to 2021. His academic background provides a strong foundation in statistical inference, experiment design, and predictive modeling, which he applies in his professional work.
Background
Prior to his current position, Tijesunimi Fatunmbi worked as a Data Scientist at Benin Electricity Distribution Plc from 2017 to 2019 in Benin-City, Edo, Nigeria. He then served as a Graduate Research Assistant at Austin Peay State University from 2019 to 2021, where he contributed to various research projects in the field of data science. His diverse experiences have equipped him with skills in data mining, machine learning, and database querying.
Achievements
Tijesunimi Fatunmbi has demonstrated a commitment to innovation in data science, particularly in developing new methodologies to tackle complex business challenges. His expertise in predictive modeling and data visualization has enabled him to derive actionable insights from data, contributing to improved decision-making processes in his roles. His strong analytical skills are complemented by a deep interest in statistics, enhancing his ability to solve unstructured business problems.