Access Bank Plc is a full service commercial Bank operating through a network of about 366 branches and service outlets located in major centres across Nigeria, Sub Saharan Africa and the United Kingdom. Listed on the Nigerian Stock Exchange in 1998, the Bank serves its various markets through 4 business segments: Personal, Business, Commercial and Corporate & Investment banking. The Bank has over 830,000 shareholders including several Nigerian and International Institutional Investors and has enjoyed what is arguably Africa's most successful banking growth trajectory in the last ten years ranking amongst Africa's top 20 banks by total assets and capital in 2011. As part of its continued growth strategy, Access Bank is focused on mainstreaming sustainable business practices into its operations. The Bank strives to deliver sustainable economic growth that is profitable, environmentally responsible and socially relevant.
Unit Head – Data Visualisation is responsible for designing, developing, and maintaining Enterprise Risk Management dashboards and data pipelines for the Bank. The role requires advanced expertise in Power BI, data modelling, and analytics, with a strong understanding of banking risk domains. The Specialist will transform complex datasets into actionable insights to support senior management decision-making, enhance regulatory compliance, and strengthen the Bank’s risk management framework.
Functions and Responsibilities
Dashboards Development & Maintenance
- Design, build, and enhance Power BI dashboards for Enterprise Risk Management (ERM) across various risk categories.
- Implement role-based access control and ensure dashboards comply with the Bank’s Access Control Framework and data security policies.
- Develop interactive reports with drill-down, filters, and dynamic visuals to support decision-making.
Data Engineering & Integration
- Build and maintain ETL/ELT data pipelines from internal and external data sources.
- Develop data models optimized for performance and scalability.
- Collaborate with IT and Risk Analytics teams to ensure data quality, consistency, and timeliness.
Data Science & Analytics
- Apply statistical models and machine learning techniques to identify risk trends and anomalies.
- Support predictive analytics for credit default, fraud detection, and operational incidents.
- Automate recurring analysis and reporting processes.
Monitoring & Governance
- Implement dashboard performance monitoring and troubleshoot issues proactively.
- Ensure compliance with internal policies, regulatory guidelines, and Basel standards.
- Maintain version control, documentation, and data lineage tracking for all dashboards.
Collaboration & Stakeholder Engagement
- Work closely with Risk Management, Finance, Compliance, and IT teams.
- Gather requirements from business stakeholders and translate them into technical solutions.
- Train and mentor team members on Power BI and analytics best practices.
Requirements
- Bachelor’s degree in computer science, Data Science, Statistics, Engineering, or related field.
- Relevant Masters' degree will be an added advantage
- Minimum of 10 years of professional experience in Data Science, and/or Data Engineering roles.
Preferred Certifications
- Microsoft Certified: Data Analyst Associate (Power BI)
- Microsoft Certified: Azure Data Engineer Associate
- Professional certifications in Risk (FRM, PRM) – desirable but not mandatory.
Skills / Competence Requirements
- Proven expertise in Power BI (DAX, Power Query, Row-Level Security, workspace management).
- Strong knowledge of SQL and data warehousing concepts.
- Experience with Python or R for analytics and modelling.
- Familiarity with Azure Data Platform (Data Factory, Synapse, Databricks) is an advantage.
- Knowledge of banking risk management concepts (credit, liquidity, market, operational, reputational risk etc.).
- Strong leadership and people management skills
- Effective in team building, coaching, and conflict resolution
- Excellent organizational, coordination, and communication abilities
- Sharp analytical thinking with a strategic, results-oriented approach
Method of Application
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