Arinze Ugwuanyi

Summary and skills. I have 5 years of experience in the data science field, First degree in electronics engineering and MSc in Data analytics. I have a vast knowledge of data science, cloud computing technology, Data Analysis, Database management, data visualization, Tableau, Power BI, ETL, MS SQL and machine learning. Hands-on, Java, and Java script. Proficient in MySQL, Microsoft Azure, and Machine learning (ML) in R programming languages. Four years of experience in Data Analysis, ETL, Data Visualisation, Data Modelling, Data Normalization and Natural language Processing (NLP). Professional in Linux and Windows login and directories. Strong skills in Data mining, Statistics analysis using (SPSS), Analytical skills, Data Extraction and Tableau. Proficiency in Salesforce, Technical customer support, building dashboard and finding the root cause analysis. Communicate effectively, pay attention to detail, teamwork play, and leadership skills, passionate about coaching, adapt to changes, and energetic to work. LANGUAGE: English and Igbo (fluent written and oral)

• Amazon Web Services (AWS): AWS certified Data analytics speciality 2022(in view).
• Amazon Web Services (AWS): AWS Cloud practitioner (in view).
• Complete Linux training course 2022. Udemy.

Enugu State University of Science and Technology, Nigeria, Bachelor's Degree (Hons), Electrical and Electronics Engineering., Oracle SQL, JAVA, System Analysis and Design, Operating Systems, Software Engineering, Modelling and simulation, Computer Architecture, Programming in C++, Networks and Telecommunications, Introduction to UNIX/Linux Systems

National College of Ireland, Dublin (NCI), Statistics for Data Analytics, Advanced data mining, Data Visualization, Data warehouse and business intelligence, data storage management, Strategic information technology and business implementation, Analytical CRM, Research in computing in all the modules programmes, Data mining, "Comparative studies analysis to identify card fraud in the financial sector. Using precision, confusion matrix and time taken to identify fraud user and legitimate user Reporting tools used: Python, Agile, R, Tableau, machine learning algorithm (Naïve Bayes, K-Nearest Neighbour, SVM and C50) and a quality report.", Data Storage management, The project aims to deploy an instance in google or Amazon EC2, Evaluate and configure the relational database system (RDS) and Non-relational database system NoSQL, and compare their performance in line with Read and write, security, Availability, throughputs, (Hadoop, MongoDB, Casandra and HBase)., MSc Thesis, "Predictive analysis on Economy class and impacts of the recession on Airlines", four machine learning algorithms were applied (Random Forest, Logistic recession, KNN and (C50) and Decision Trees) and data governance in the extraction dataset. Data modelling was applied, divided the dataset into testing and training data Tools used. R Programming, Tableau, and Machine Learning., Data warehouse Projects, "Modern Agricultural practice and resource management". A prototype of a data warehouse on modern agricultural practice and resource management. Requirements: 3 different data sources (Two structural and one unstructured data source), ETL testing process and automation and written report. Reporting tools: SQL, SSIS, Microsoft server software, R and Tableau

Innovation skills, mentorship, artificial intelligence (AI) and its applications. Have demonstrated a passion for innovative technologies that are data-driven to solve problems. Participate in soccer and table tennis during leisure time and listen to business news.