Jan 2024 – Aug 2025 · 1 yr 7 mos · Lagos State, Nigeria · Hybrid

• Led the selection and direction of large datasets using graphical and metadata tools.
• Ensured data accuracy, integrity, and tracking standards.
• Supported the development and automation of dynamic, machine-learning–driven comparison systems.
• Conducted data quality assessments and testing procedures
• to validate all monitoring systems.
• Collaborated with cross-functional teams to define data requirements and establish data structures that align with business objectives.
• Designed and maintained advanced data visualization dashboards to track key performance indicators and operational metrics, enabling visibility across departments.
• Researched and monitored industry trends and advancements in data analysis, storage, and automation to improve analytical processes and tools.
• Developed an end-to-end analytics platform to enhance data-driven decision-making across stakeholders.

Oct 2023 – Dec 2023 · 2 mos · Remote

• ·       Monitored and led the analysis of business expenditures at country and site levels, ensured precision and compliance to financial guidelines.
• ·       Developed and maintained robust tracking systems for efficient data oversight and streamlined data processes.
• ·       Contributed to the design and implementation of data models that automated the cleaning and processing of financial data, enhancing accuracy and reliability.
• ·       Provided in-depth financial data analysis to inform decision-making and support business goals.
• ·       Stayed updated on industry trends and advancements in data analytics and automation to continually improve support processes.

Jan 2023 – Sep 2023 · 8 mos · Nigeria · Hybrid

• ·       Designed a comprehensive and expertly structured curriculum that covers essential concepts and advanced skills in data analysis, thoughtfully selecting high-quality resources, textbooks, and software tools to optimize learning outcomes.
• ·       Delivered dynamic and engaging lectures, demonstrations, and interactive discussions that break down complex data analysis concepts, making them accessible and actionable for students of all levels.
• ·       Fostered a positive, inclusive, and collaborative classroom environment that encourages student engagement, critical thinking, and active participation.
• ·       Created and administered meaningful assessments, including quizzes and hands-on projects, to effectively gauge students' understanding, track their progress, and provide targeted feedback.
• ·       Consistently committed to professional growth, actively participating in workshops, conferences, and webinars to refine instructional methods and stay current with the latest advancements in data analysis, ensuring students receive the most relevant and impactful education.
• ·       Provided personalized mentorship and career guidance to students, helping them identify strengths, set goals, and navigate career pathways in data analysis.
• ·       Organized study groups, forums, and collaborative activities to foster a strong learning community, encouraging students to support each other and share knowledge.
• ·       Continuously refined and updated the curriculum based on industry trends, incorporating cutting-edge tools and real-world case studies to ensure practical and relevant learning experiences.

Dec 2021 – Nov 2022 · 11 mos · Remote

• ·       Collected and preprocess large, structured, and unstructured datasets from multiple sources (e.g. databases, APIs, web scraping).
• ·       Ensured data quality and integrity by performing data cleaning, transformation, and normalization.
• ·       Conducted in-depth exploratory data analysis to uncover trends, correlations, and patterns.
• ·       Created visualizations and reports to communicate data insights and key findings to stakeholders.
• ·       Built, tested, and deployed predictive models, including regression, classification, clustering, and time-series analysis.
• ·       Designed and conducted A/B tests and experiments to validate hypotheses and optimize business processes.
• ·       Applied statistical methods to evaluate experiment results, ensuring data-driven decision-making.
• ·       Translated complex business challenges into data-driven problems and identify solutions.
• ·       Collaborated closely with business stakeholders to understand requirements and deliver actionable insights that drive business outcomes.
• Present findings and recommendations to non-technical stakeholders, making complex information accessible and actionable.