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Data Analyst with 1+ years in SQL & Python
Data Analyst with experience transforming complex datasets into actionable insights that drive operational, financial, and strategic decision-making. Proficient in SQL, Python, Excel, Google Sheets, and BI tools for structured data modeling, dashboard development, and performance monitoring. Experienced in trend analysis, forecasting, and cost evaluation across cross-functional teams, with a strong emphasis on data accuracy, quality assurance, and critical thinking to deliver measurable performance improvements.
ALX AFRICA
DATA SCIENCE CERTIFICATE · Data Science
August 1, 2025 – Present
University of Cassino and Southern Lazio
MASTERS DEGREE IN ECONOMICS · Economics
August 1, 2025 – June 30, 2025
CISCO
DATA ANALYTICS COURSE · Data Analytics
August 1, 2024 – June 30, 2025
ICT Authority Of Kenya
DATA ANALYTICS TRAINING · Data Analytics
August 1, 2023 – June 30, 2023
Kirinyaga University
BACHELOR OF SCIENCE IN STATISTICS · Statistics
August 1, 2017 – June 30, 2022
JACARANDA MATERNITY HOSPITAL
DATA & PERFORMANCE ANALYST
October 8, 2024 – Present
Nairobi, Nairobi, Kenya
AMPERSAND E MOBILITY
DATA ANALYST
February 12, 2024 – October 4, 2024
Nairobi, Nairobi, Kenya
GEOTHERMAL DEVELOPMENT COMPANY
STATISTICIAN INTERN
May 12, 2023 – February 9, 2024
Nairobi, Nairobi, Kenya
World Bank Economic Indicators Analysis
June 17, 2026 – Present
Macroeconomic Data Engineering & Analysis Pipeline Designed and implemented an end-to-end ETL pipeline to extract macroeconomic indicators (GDP, population, inflation, unemployment) from the World Bank API and load structured data into a relational MySQL database. Built a modular, scalable data pipeline with automated pagination handling, ISO3 country validation, metadata-driven filtering, and idempotent upsert logic to ensure reliable re-execution and long-term trend consistency. Engineered a normalized database schema with composite primary keys (country_code, year, indicator_code) to prevent duplication and enable accurate country-year-indicator tracking. Implemented bulk data ingestion using optimized executemany() operations, improving pipeline efficiency and scalability for multi-country, multi-year datasets. Structured and classified aggregate entities (World, Regions, Income Groups) using custom flags to support clean cross-country comparisons and macroeconomic benchmarking. Applied exploratory data analysis and regression techniques to evaluate relationships between GDP growth, unemployment trends, inflation patterns, and population dynamics. Designed analytical use cases to assess economic strategy effectiveness, sustainable growth patterns, and long-term development trajectories. Created a Power BI presentation by integrating Power BI with the MySQL database to visualize and analyze macroeconomic patterns in population growth, unemployment, inflation, and comparative country performance over time.
View ProjectEnd-to-End Analytics & Data Engineering Pipeline (API → MySQL → BI)
June 17, 2026 – Present
Designed and implemented a modular ETL pipeline to extract structured JSON data from a public API, transform nested records using Python (Pandas), and load validated datasets into a relational MySQL database. Engineered a normalized schema with fact and dimension tables (players, teams, events, player_gameweek_stats) to support scalable querying and consistent analytical modeling. Developed reusable SQL views to define core business logic including ROI (points per cost), performance per 90 minutes, reliability thresholds, positional benchmarking, and elite classification logic. Applied bias-control techniques by excluding low-minute records and enforcing minimum playing-time thresholds to ensure statistical reliability and fairness in comparisons. Built interactive dashboards in Metabase to support constrained decision optimization under a fixed budget scenario, enabling value-based asset selection modeling. Implemented automated weekly pipeline execution using Windows Task Scheduler, ensuring idempotent data ingestion, duplicate protection, and continuous season-long updates. Structured analytics to evaluate short-term trends, week-over-week variance, positional contribution patterns, and player efficiency benchmarking.
View ProjectAchieved a perfect score (100%) on the Power BI assessment, indicating comprehensive mastery of the tool and related concepts.
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Cultural Fit Analysis
The candidate's project diversity, ranging from macroeconomic indicators to sports analytics and healthcare KPIs, shows a broad interest and adaptability to different domains. Their experience in both corporate (Ampersand E Mobility, Jacaranda Maternity Hospital, Geothermal Development Company) and personal projects demonstrates initiative and a continuous learning mindset. The role alignment with 'Data Analyst' is strong, given their direct experience and educational background in Statistics and Data Analytics. The breadth of skills (SQL, Python, R, Power BI, Looker Studio, Metabase, Azure) indicates a versatile individual who can contribute across various data initiatives. The ongoing education in Data Science and Economics further highlights a commitment to continuous professional development.
Soft Skills & Operational Fit
The candidate demonstrates strong critical thinking and structured problem-solving abilities, essential for a senior Data Analyst. Their experience in collaborating with cross-functional teams and presenting insights to executive leadership indicates good communication and stakeholder management skills. The emphasis on data accuracy, quality assurance, and delivering measurable performance improvements aligns well with operational excellence. The psychometric test score (337/500) suggests a moderate fit in areas like logical reasoning and work attitude, which could be further explored in an interview.
Scored 80% on the Odoo Techno-Functional Test, indicating a strong grasp of Odoo's functionalities, though not absolute mastery.
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Achieved a perfect score (100%) on the Data Engineer — Azure assessment, indicating comprehensive mastery of Azure data engineering concepts including Databricks DLT, streaming, and cost management.
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