Wisdom Udo, a Senior Data Scientist at BT Group in the UK is a shining example of how expertise and innovation can drive significant advancements in technology. As a Nigerian professional making remarkable strides in the field of data science and engineering, Udo’s work is not only transformative but also novel, setting new benchmarks in network optimization and data-driven solutions.
Wisdom Udo’s academic journey laid a strong foundation for his illustrious career.
He earned an M.Sc. in Artificial Intelligence from Teesside University, United Kingdom, and a Bachelor’s degree in Production Engineering (Mechanical) from the University of Benin. His academic excellence is further demonstrated by prestigious awards such as the Eni Postgraduate Scholarship Award for Excellence and the Exxon Mobil Undergraduate Scholarship Award for Excellence. These accolades highlight his dedication and outstanding performance throughout his educational journey.
Since May 2023, Udo has been a pivotal figure at BT Group, where he leads projects to optimize network performance using advanced data science techniques and MLOps best practices. His work addresses critical issues of high latency and low throughput in BT Group’s network, which faced congestion and uneven traffic distribution. By managing vast amounts of incomplete and noisy data, Udo implemented automated data pipelines using Python, Kafka, and MongoDB. He utilized Spark for distributed processing and Airflow for orchestrating data cleaning tasks, ensuring continuous and accurate data flow from network operations, customer interactions, and performance metrics.
In developing predictive models for network optimization, Udo’s innovative use of Python, TensorFlow, and XGBoost, coupled with MLflow for tracking experiments and versioning models, ensured reproducibility and effective management of the machine learning lifecycle. His meticulous approach led to significant improvements in network performance, including an 11% reduction in network latency, a 15% increase in throughput, and a 25% decrease in downtime frequency.
These enhancements have not only boosted network efficiency but also resulted in a 21% rise in positive customer feedback, establishing BT Group as a leader in network management technology. Before joining BT Group, Udo worked as a Data Engineer on contract at Amazon, specifically within Twitch Sales Data and Analytics.
His role involved building and optimizing modeling infrastructure to support Twitch advertising. He developed enterprise-grade model pipelines utilizing AWS services such as SageMaker, Redshift, and Glue, addressing the challenge of scaling machine learning tasks to handle vast amounts of data efficiently. His efforts led to a 15% reduction in operational costs and a 21% improvement in user engagement through the development of a sophisticated recommender system. Udo’s contributions at Amazon also included the development of a robust A/B testing framework to evaluate various ad strategies.
By automating the integration of new test configurations, model deployment, and execution phases using AWS CodePipeline, he maintained continuous deployment cycles, ensuring minimal downtime. His expertise in real-time data collection and processing using Amazon Kinesis enabled swift adjustments based on test outcomes, enhancing the reliability and validity of test results. Prior to his tenure at Amazon, Udo served as a Data Engineer at the University of Salford. There, he developed an advanced sound classifier using AWS, integrating acoustics expertise with machine learning for effective noise classification and analysis. His work involved gathering extensive audio samples, applying noise reduction techniques, and extracting features using Python’s LibROSA. He trained models using TensorFlow on an EC2 instance with GPU support, achieving high performance through meticulous tuning of hyperparameters.
Udo’s technical skills are extensive and diverse. He is proficient in programming languages such as Python, R, JavaScript, and jQuery, and has sound knowledge of cloud infrastructure, including AWS and Azure. His expertise in data visualization tools like Plotly, Matplotlib, PowerBI, and Tableau, along with big data technologies such as Apache Hadoop and Spark, has been instrumental in his projects. Additionally, his knowledge of SQL and machine learning frameworks like scikit-learn, TensorFlow, and PyTorch has enabled him to handle large datasets and develop complex analytical models. Throughout his career, Udo has been recognized for his excellence and contributions to the field. He has received prestigious awards, including the Eni Postgraduate Scholarship Award for Excellence and the Exxon Mobil Undergraduate Scholarship Award for Excellence.
His memberships in professional organizations such as the British Computer Society (BCS), Royal Statistical Society (RSS), and Institute of Electrical and Electronic Engineers (IEEE) further attest to his standing in the field. Udo’s research contributions are significant, with numerous publications in reputable journals. His work on “Data-Driven Predictive Maintenance of Wind Turbine Based on SCADA Data,” published in IEEE Access, and “Theoretical Approaches to Data Analytics and Decision-Making in Finance: Insights from Africa and the United States,” published in GSC Advanced Research and Reviews, highlight his expertise in applying data science to practical problems.
His research on “Conceptualizing Emerging Technologies and ICT Adoption: Trends and Challenges in Africa-US Contexts” and “The Role of Theoretical Models in IoT-Based Irrigation Systems” further demonstrate his commitment to advancing the field of data science. Udo’s scholarly impact is evident in his citation metrics. His research has been cited 114 times, reflecting the high relevance and influence of his work within the academic community. His ability to translate complex data science concepts into practical applications has garnered recognition and respect from peers and industry professionals alike.
In addition to his research, Udo has made significant contributions as a peer reviewer for several journals, including the Computer Science & IT Research Journal and the International Journal of Management & Entrepreneurship Research. His expertise in adaptive neuro-fuzzy inference systems, clean data, and data-driven predictive maintenance has been invaluable in these roles. Udo’s extensive experience, technical expertise, and innovative approach have made him a leader in the field of data science and engineering.
His contributions to optimizing network performance at BT Group, developing advanced modeling infrastructure at Amazon, and pioneering research in data analytics have had a significant impact on the industry. As he continues to push the boundaries of what is possible with data science, Udo’s work promises to drive further advancements and innovations in the field. Wisdom Udo’s fellowship in esteemed organizations such as the Nigerian Institute of Professional Engineers and Scientists (NIPES), the Institution of Data Scientists and Analysts (IDSA), and the Institute of Management Consulting (IMC) further highlight his commitment to professional excellence and his contributions to the field.
These fellowships are a testament to his expertise and dedication to advancing data science and engineering. In summary, Wisdom Udo is a trailblazing Nigerian data scientist whose work in the UK is revolutionizing network performance and data-driven solutions. His innovative approaches, extensive technical skills, and significant contributions to research and industry practice make him a standout figure in the field. As he continues to lead groundbreaking projects and drive advancements in data science, Udo’s impact is set to inspire and influence the next generation of data scientists and engineers.