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Japhlet Ndiawo

@japhletndiawo

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Data Analyst at National Bank of Kenya, turning customer and service data into banking performance insights.

Kenya

Message

At National Bank of Kenya, I prepare Customer Experience management reports and calculate CES, NPS, and CSAT indicators. I analyze service levels, complaints, and turnaround times across loans, account services, and payments to surface trends and customer pain points.

Earlier, as a Direct Sales Representative at National Bank of Kenya, I automated daily reporting tools, reducing reporting time by 30%. At Kenya National Bureau of Statistics, I used R and SQL to support analysis and preparation of a county statistical abstract.

Experience

Work history, roles, and key accomplishments

Current

Data Analyst - Customer Experience

Current

National Bank of Kenya

Mar 2025 - Present (1 year 7 months)

Owns preparation and calculation of Customer Experience management reports, translating operational and customer-feedback data into performance insights. Calculates CX metrics including CES, NPS, CSAT, service levels, and turnaround times.

Excel SQL R Power BI KPI Reporting Trend Analysis Data Quality Customer Experience Analytics CES NPS CSAT Stakeholder Communication

Direct Sales Representative

National Bank of Kenya

Jan 2020 - Feb 2025 (5 years 1 month)

Analyzed sales and customer feedback data to support targeting and product positioning. Automated daily reporting tools, reducing reporting time by 30% and surpassing monthly sales targets by 20%.

Sales Analytics Customer Needs Analysis Report Automation Excel Mentorship

IT Support Intern

Dala FM

Jun 2019 - Sep 2019 (3 months)

Implemented a support-ticketing approach that reduced response time for technical requests by 20%. Supported system upgrades, software deployment, and troubleshooting.

IT Support Troubleshooting System Upgrades Software Deployment Corporate Trainer

Data Analysis Intern

Kenya National Bureau of Statistics

Jun 2017 - Sep 2017 (3 months)

Coordinated field data collection covering over 500 rural households and reviewed submissions for completeness and accuracy. Improved data-entry processes, reducing recorded errors by 15%.

Data Collection Data Quality R SQL Statistical Analysis