Credit Rating Model
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Summary
Built a SAS-based statistical model to predict corporate bond credit ratings using firm-level financial ratios and capital structure data.
Results-driven data analytics professional adept at leveraging SQL, Python, and dbt to build scalable data pipelines, develop intuitive dashboards, and deliver actionable insights. Proficient in advanced data visualization tools and machine learning, Mmesoma excels at cross-functional collaboration to drive product development and strategic business decisions in fast-paced, agile environments.
Data Engineer
Washington, District of Columbia, US
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Summary
Led the design and deployment of an LLM-powered ETL pipeline to transform unstructured educational data for 60+ partner institutions, significantly enhancing data accessibility and consistency.
Highlights
Designed and deployed an LLM-powered ETL pipeline using the Gemini API, transforming unstructured educational data into CTDL-compliant formats for 60+ partner institutions.
Built scalable ingestion tools with Python and Flask, reducing partner onboarding time by 80% and enabling seamless integration for non-technical users.
Implemented schema validation, mapping, and audit traceability, ensuring data accuracy and regulatory compliance across data processes.
Led Agile sprint collaborations with stakeholders, integrating feedback for continuous pipeline improvements and feature enhancements.
Strategy Analyst
Champaign, Illinois, US
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Summary
Delivered actionable reporting insights and visualizations on AI-driven electricity demand, directly supporting strategic decisions for Fortune 500 energy sector clients.
Highlights
Analyzed complex AI-driven electricity demand data to generate actionable reporting insights and visualizations for Fortune 500 energy sector companies.
Designed and analyzed a student accessibility survey (n=34) using Qualtrics and Excel, identifying behavioral trends that informed adaptive program feasibility.
Data Analyst
Lagos, Lagos, Nigeria
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Summary
Optimized data extraction and visualization processes for the Ministry of Housing, improving resource allocation and reporting efficiency across 15+ local government areas.
Highlights
Wrote and optimized SQL queries to extract critical data from the ministry's housing database, supporting weekly updates on construction timelines and fund disbursement.
Monitored occupancy rates and housing demand trends, contributing to the reallocation of resources to high-need districts and improving unit utilization by 18%.
Developed and maintained interactive Tableau dashboards to visualize housing project progress across 15+ local government areas, reducing reporting time by 30%.
Market Research Analyst
Cape Town, Western Cape, South Africa
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Summary
Conducted comprehensive market research and competitive analysis, generating insights that enhanced customer engagement and refined market positioning strategies.
Highlights
Conducted customer surveys with 100+ respondents, generating insights that increased customer engagement by 15%.
Analyzed 60+ competitors in Nigeria, producing detailed reports that improved market positioning and pricing strategies.
Machine Learning Intern
Lagos, Lagos, Nigeria
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Summary
Supported the development and pilot deployment of machine learning solutions to enhance crop health classification and improve data-driven agricultural management.
Highlights
Enhanced crop health classification model precision by 20% through annotation of 10,000+ labeled images.
Supported pilot deployment of machine learning tools to 500+ farmers, enabling data-driven crop management decisions.
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Master of Science (STEM)
Business Analytics
Grade: 4.0/4.0
Courses
Big Data Analytics
Enterprise Database Management
Big Data Infrastructure
Financial Risk Management
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Bachelor of Science
Electrical and Electronics Engineering
Grade: 4.38/5.0
Issued By
Amazon Web Services
Issued By
Python, SQL, Bash, R, SAS.
AWS, Airflow, dbt, Databricks, Spark, Terraform, Git, Tableau, Power BI.
Data Modeling, CI/CD, Data Visualization, Machine Learning, Statistical Analysis.
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Summary
Built a SAS-based statistical model to predict corporate bond credit ratings using firm-level financial ratios and capital structure data.
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Summary
Engineered an event-driven architecture with AWS Kinesis, Lambda, and DynamoDB to process 5,000+ events/hour.
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Summary
Developed a real estate price forecasting pipeline using regression and random forest models.