MARTIN DIARUA
www.linkedin.com/in/martin-diarua- | github.com/Martin-analytics
Professional Summary
Data Analyst specializing in insight generation, dashboard development, and translating complex datasets into
actionable strategies. Proven ability to architect end-to-end analytical pipelines, evaluate campaign performance,
and confidently present technical findings to diverse, non-technical stakeholders. Highly proficient in Power BI,
SQL, and Python for tracking trends and supporting data-driven decision-making.
Education
University of Nigeria
Bachelor of Science in Pure and Industrial Chemistry, Minor in Mathematics
Coursera
Python Programming
Nsukka, NG
Aug. 2020 – Dec 2024
Online
May. 2025 – Sept. 2025
Udemy
Data Science
Online
Oct. 2025 – Jan. 2026
Technical Portfolio
Stakeholder Retention Prediction Model | Python, Pandas, Scikit-Learn, XGBoost
Mar 2026
• Built an end-to-end analytics system to evaluate engagement trends and predict future stakeholder
involvement using time-based modeling
• Applied K-Means segmentation to identify key behavioral drivers and support targeted communication
strategies
• Translated complex predictive probabilities into clear, non-technical insights to evaluate campaign
performance
Stakeholder Segmentation & Insight Pipeline | Python, Pandas, KMeans, Data Visualization Mar 2026
• Developed a full data pipeline for stakeholder segmentation, including data cleaning, transformation, and
feature engineering
• Applied clustering techniques to group stakeholders into distinct behavioral personas based on
engagement patterns
• Designed accessible visual reports to help cross-functional teams translate analysis into practical
improvements
Engagement Drop-off Prediction Analysis | Python, Pandas, Random Forest, EDA
Mar 2026
• Built a predictive model on demographic and behavioral data to identify stakeholders at risk of
disengagement
• Addressed class imbalance to ensure dataset reliability for ongoing analysis and monitoring frameworks
• Delivered actionable insights to support proactive retention strategies and maintain a consistent
engagement culture
Technical Skills
Languages and Tools: SQL (MySQL), Python, Microsoft Power BI, Excel
Techniques: Dashboard Development, Insight Generation, Data Cleaning, Statistical Analysis, Segmentation
Libraries: Pandas, NumPy, Matplotlib, Scikit-learn, Seaborn
Machine Learning: Regression, Classification, Clustering (K-Means)
