MOHD JAHIDUL HOQUE
A technology and analytics professional with a multidisciplinary background spanning Computer Science, Software Engineering, and Business Analytics. My academic journey—from earning a Bachelor of Science in Computer Science & Engineering to completing a Master of Science in Business Analytics with a 4.00 GPA—reflects a commitment to integrating technical expertise with data-driven decision-making. My graduate research, peer-reviewed publication, and professional experience have strengthened my interest in Artificial Intelligence, Machine Learning, Business Intelligence, and Decision Support Systems. I aspire to pursue doctoral research that advances intelligent technologies for organizational decision-making, digital transformation, and cybersecurity. My long-term vision is to bridge academic research with practical business innovation while preparing for leadership roles as a technology executive and entrepreneur.
To pursue doctoral research in Information Technology with a focus on Artificial Intelligence, Machine Learning, Decision Support Systems, Cybersecurity, and Digital Transformation. My objective is to develop intelligent, data-driven solutions that enhance organizational decision-making while contributing meaningful research to both academia and industry.
Skills
Education
Master of Science - Business Analytics
Selected Graduate Coursework
- Machine Learning
- Business Intelligence
- Predictive Analytics
- Data Visualization
- Business Analytics
- GPA: 4.00 / 4.00
Bachelor of Science - Computer Science & Engineering
Work History
Data Analyst
3 Months- Collected, cleaned, validated, and analyzed operational datasets.
- Generated analytical reports supporting business intelligence and decision-making.
- Assisted stakeholders by identifying trends through data visualization and reporting.
- Improved reporting accuracy through systematic data validation and quality assurance.
Junior Software Developer
3 Years- Designed, developed, tested, and maintained software applications supporting business operations.
- Collaborated with multidisciplinary development teams throughout the software development lifecycle.
- Worked extensively with SQL databases for application development, maintenance, and optimization.
- Participated in debugging, testing, deployment, and performance optimization activities.
- Assisted in improving software reliability, scalability, and operational efficiency.
Languages
RESEARCH EXPERIENCE
- Graduate Research – Master's Capstone
- Grand Canyon University
- Customer Churn Prediction in the Telecommunications Industry
- Conducted graduate-level research focused on applying machine learning techniques to predict customer churn and improve organizational decision-making.
- Research Activities
- Conducted a comprehensive literature review on customer churn prediction, predictive analytics, and customer retention strategies.
- Collected, cleaned, transformed, and analyzed telecommunications customer datasets using SQL and Python.
- Applied the CRISP-DM methodology throughout the research lifecycle, including business understanding, data preparation, modeling, evaluation, and deployment planning.
- Designed, trained, and evaluated multiple supervised machine learning classification models using Scikit-learn.
- Performed feature engineering, exploratory data analysis (EDA), and model performance evaluation.
- Developed interactive dashboards and analytical visualizations using Tableau and Microsoft Power BI.
- Documented research methodology, findings, limitations, and recommendations within a formal graduate research report.
- Generated actionable business recommendations to improve customer retention through predictive analytics.
ACADEMIC STRENGTHS
- Master of Science in Business Analytics with a 4.00 GPA
- First author of a peer-reviewed journal publication
- Graduate research experience in machine learning and predictive analytics
- Strong interdisciplinary foundation in Computer Science and Business Analytics
- Practical experience in software engineering and business analytics
- Experience applying AI-driven techniques to real-world business problems
RESEARCH INTERESTS
- Artificial Intelligence (AI)
- Machine Learning
- Business Analytics
- Decision Support Systems
- Business Intelligence
- Information Systems
- Digital Transformation
- Cybersecurity
- Predictive Analytics
- Data-Driven Decision Making
SELECTED PUBLICATION
- Hoque, M. J., Akter, F., & Mohammad, A. R. (2019).
- Data-Driven Decision Support System for Restaurant Business Optimization.
- American Journal of Economics and Business Management, 2(2).
- Global Research Network LLC (USA).
- Google Scholar
- Https://scholar.google.com/citations?user=ffyNMxoAAAAJ