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National Bank of Kenya
Banking + 2 more
Description
Education/Professional Qualifications, Skills & Experience:
- Bachelors’ Degree in Data Analytics, IT or Business related from a recognized University.
- Master’s degree in a Business-related field from a recognized University is an added advantage
- 5 years of Commercial Banking experience, of which at least 3 years in Business analysis.
- Have appreciation and operating knowledge of the banking industry, market, trends as well as challenges.
- Demonstrable cross-cultural, people and relationship management skills, networking and negotiation skills, team motivation and leadership competence.
- Strong analytical skills.
- Stakeholder Management
- Strong knowledge of local Islamic banking market and vision about future direction and market sensitivities.
- Excellent interpersonal, communication and presentation skills
- Some knowledge of the Bank’s lending principles, policies and procedures
- Ability to prioritize, meet deadlines and work under pressure.
- Innovative and creative - ability to think creatively and develop innovative solutions.
- Ability to make operational and routine decisions in a timely and effective manner.
- Able to withstand operational challenges and maintain momentum.
- Manages emotions in a mature and composed manner as expected.
Send your CV and application letter showing how you meet the role requirement stated above. Indicate Name of Job on email subject.
Responsibilities
- Develop and maintain dashboards and reports using BI tools such as Power BI.
- Monitor key performance indicators (KPIs) and provide regular updates to stakeholders.
- Integrate Power Platform tools (Power Apps, Power Automate) to digitize and streamline reporting processes.
- Translate business requirements into robust datasets using SQL and other data management tools.
- Enhance the division’s ability to anticipate performance trends and support proactive commercial decisions.
- Build forecasting and predictive models for deposit growth, loan demand, and customer acquisition using machine learning.
- Conduct deep-dive analysis of customer behavior, transaction patterns, and product performance.
- Generate ad hoc reports as requested by the teams.
- Collaborate with IT and data protection teams to ensure data quality, governance, and security.
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