Augustine Nwenewor

Managed key client relationships and drove business growth through strategic onboarding, training, and customer retention initiatives for a leading fintech platform.

• Drove 20% growth in transaction volume within one month by optimizing client onboarding processes.
• Delivered comprehensive training to over 50 merchants monthly, consistently achieving a 95% satisfaction rate.
• Collaborated with product and operations teams to reduce customer churn by 30% through targeted interventions.
• Identified and capitalized on upsell opportunities, contributing to a 15% increase in monthly recurring revenue.

Analyzed complex sales and operations data to deliver actionable insights, improving client ROI and optimizing marketing strategies for a technology solutions provider.

• Analyzed sales and operations data, improving client Return on Investment (ROI) by 18% through data-driven recommendations.
• Developed and deployed Power BI dashboards for real-time decision-making, serving over 10 diverse clients.
• Cleaned and validated over 500,000 rows of raw data, enhancing overall data accuracy by 95%.
• Led customer behavior analysis initiatives, improving targeted marketing campaign effectiveness by 22%.

Managed a large portfolio of client accounts, consistently exceeding sales targets and enhancing product visibility for a leading e-commerce platform.

• Managed over 200 client accounts, increasing sales by 25% month-over-month through effective relationship management.
• Consistently surpassed sales targets, achieving over 120% of goals for three consecutive quarters.
• Onboarded more than 100 new vendors and improved product visibility by 15% on the platform.

Analyzed survey data to identify trends in salary, satisfaction, and skills, segmenting insights by demographics and roles for strategic insight.

Explored infection, vaccination, and mortality trends using SQL (CTEs, window functions) to uncover region-specific public health insights.

Created an interactive Tableau dashboard to compare regional sales performance, highlight key metrics, and recommend sales strategy optimization.

Personal loans are a high‑margin product for banks, but only if marketing data is reliable and reusable. This Python pipeline cleans and standardizes a raw campaign extract (bank_marketing.csv) so the bank can load it into PostgreSQL and easily append future campaigns without rework. It enforces consistent schemas and data types, fixes common quality issues, and outputs three final, analysis‑ready CSVs.