Ango Steven. Komba-
github.com/Skango
linkedin.com/in/steven-ango
Detail-oriented and analytical Data Analyst with a strong background in data analysis, seeking to
leverage quantitative skills to drive informed business decisions. Proficient in SQL, Python, and data
visualization tools like Power BI. Experienced in optimizing sales strategies, conducting market
research, and implementing predictive models. Eager to apply statistical methods and predictive
analysis to optimize strategies and enhance operational efficiency.
SKILLS
Programing Languages: Python , SQL
Frameworks/Technologies: BeautifulSoup, Pandas, Numpy, Matplotlib, Seaborn, Tableau, PowerBI, Microsoft
Excel, Docker, Gitlab, Google API.
OS/Tools: AWS, Git/Github, MySQL, Snow akes.
Soft Skills: Analytical thinking , Critical thinking, Communication, Culture awareness, Emotional intelligence,
Growth mindset, Leadership, Storytelling, Time management.
EXPERIENCE
Data-Expo | Kaduna, Nigeria — Junior Data Analyst
Dec 2023 - Present
● Monitored, assessed, and measured the success of improvements and system solutions, providing
feedback for further enhancements.
● Conducted in-depth analysis of student engagement data, resulting in a 10% increase in average daily
student engagement metrics and a 15% improvement in retention rates for courses with targeted
interventions based on analysis findings.
● Assisted in the development and validation of predictive models for student performance, leading to
a 20% increase in the accuracy of midterm grade predictions and a 25% reduction in dropout rates
through early identification of at-risk students.
● Collaborated with cross-functional teams to create interactive dashboards and visualizations, resulting
in a 30% decrease in time spent by stakeholders to access and interpret key metrics and a 40% increase
in user engagement with data-driven insights, as measured by dashboard interaction metrics.
Federal Mortgage Bank of Nigeria| Abuja,Nigeria — Data Analyst
Dec 2021 - Nov 2022
● Planned and executed the full implementation of solutions, adhering to project timelines and
objectives
● Spearheaded data analysis initiatives, resulting in a 15% increase in risk assessment accuracy, a 20%
improvement in financial forecasting precision, and a 25% boost in operational efficiency.
● Engineered predictive models, leading to a 10-point increase in customer service satisfaction scores, a
30% reduction in process cycle time, and a 15% improvement in resource utilization.
● Fostered collaboration across departments, resulting in a 30% increase in the number of actionable
insights generated, a 25% improvement in decision-making turnaround time, and a 20% increase in
cross-functional team satisfaction ratings.
● Identified underlying problems and root causes in business processes and operations, facilitating
targeted solutions.
EDUCATION
Federal University of Technology Minna, Nigeria — B.Tech. Geology
2014 - October 2019
● Relevant Coursework: Geostatistics and Spatial Analysis, Remote Sensing and Image
Analysis, Geological Data Visualization.
● Project Work: Led a comprehensive project analyzing soil composition data and historical
flood records, applying skills in geostatistics and spatial analysis. Developed a data-driven
model to predict areas prone to flooding, utilizing techniques learned in relevant
coursework. Contributed valuable insights for urban planning and disaster response
strategies through the application of geostatistics, spatial analysis, and geological data
visualization.
CERTIFICATIONS
Google (Coursera) — Google Data Analytics Certificate, Oct 2022 – March 2023
University Of Michigan (Coursera) — Python for Everybody, Jan 2023 – Nov 2023
PROJECTS
Sales Performance Dashboard (Power BI/Tableau/SQL/Excel)
● Designed and built an interactive sales performance dashboard using Power BI/Tableau,
enabling data exploration and fostering data-driven decision making (quantify impact if
possible).
● Created user-friendly tutorials for colleagues, empowering them with hands-on experience in
data extraction, transformation, and loading (ETL) using SQL queries.
● Demonstrated expertise in data analysis and visualization by crafting a customized
dashboard theme in Tableau, resulting in clear and actionable insights.
Exploratory Data Analysis of Apple App Store (SQL)
● Conducted a comprehensive exploratory data analysis of the Apple App Store dataset using
SQL.
● Cleaned and preprocessed the data to ensure accuracy and facilitate analysis.
● Identified key trends and relationships between app categories, ratings, price, and user
reviews.
● Utilized various SQL techniques including joins, aggregations, and filtering to uncover
valuable insights for app developers and marketers.
● Presented findings in clear reports and visualizations, enabling stakeholders to make datadriven decisions regarding app development and marketing strategies.
Personal Finance Analysis Dashboard (Python , Pandas, NumPy, Google Sheets API)
● Developed an interactive dashboard using Python to analyze personal finance data.
● Provides a comprehensive view of financial transactions, categorized expenses, and spending
trends over time.
● Data Retrieval & Cleaning: Connects to Google Sheets via API, retrieves transaction data,
and performs data cleaning for accurate analysis.
● Interactive Visualizations (Panel, HvPlot, or Holoviews):
○ Summary Banner: Key metrics like income, expenses, and savings for the previous
month.
○ Expense Breakdown Chart: Visualizes last month's spending distribution across
categories.
○ Expense Trend Chart: Tracks spending trends with category ltering options.
○ Transaction Table: Detailed records with date, category, description, and amount.
