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Junior Data Analyst with less than a year in data modeling, visualization, and Python.
Analytically-minded and detail-oriented Educational Management graduate transitioning into Data Analytics. Possesses a strong foundation in structured problem-solving, quantitative research methodologies, and spreadsheet data management. Highly proficient in translating raw, complex datasets into actionable business or organizational insights using Advanced Excel, Power BI, and Python. Proven ability to clean messy unstructured records, analyze performance trends, and build interactive dashboards that support data-driven decision-making. Eager to leverage technical skills and fresh perspectives in a remote Junior Data Analyst role.
Enugu State University of Science and Technology (ESUT)
B.Sc. · Educational Management
N/A – June 30, 2026
Automated Data Transformation & Cleaning Pipeline
June 1, 2026 – June 1, 2026
Successfully developed a structured Python data pipeline to ingest, clean, and standardize irregular transactional datasets, resolving structural discrepancies and missing records. Engineered custom scripts using the Pandas library to handle complex data type transformations and filter operational parameters. Optimized reporting ingestion times by formatting data into clean, normalized structures ready for downstream visualization tools.
Academic Performance & Enrollment Analysis Dashboard
January 1, 2026 – January 1, 2026
Engineered an interactive dashboard modeling institutional growth, tracking student performance benchmarks, and profiling departmental resource utilization. Cleaned and pre-processed fragmented education-sector records using Power Query to eliminate structural errors and duplicate entries. Authored custom DAX measures in Power BI to calculate dynamic year-over-year enrollment growth and attrition trends.
Data Analytics Professional Track
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background in Educational Management, combined with a transition into Data Analytics, suggests adaptability and a proactive learning mindset. The projects, though academic, demonstrate a practical approach to problem-solving and a willingness to apply technical skills to diverse datasets. The ongoing certification further emphasizes a commitment to continuous learning, which is a positive indicator for cultural fit in a dynamic technical environment.
Soft Skills & Operational Fit
The candidate highlights structured problem-solving, analytical thinking, quantitative research, cross-functional communication, and team collaboration as soft skills. These are well-aligned with the demands of a Junior Data Analyst role, indicating a good operational fit for collaborative and analytical environments.