Sunday, May 6, 2018

Head of Data Management and Analytics at NMB Bank Plc, May 2018

Head of Data Management and Analytics at NMB Bank Plc, May 2018


Data Management & Analytics team: is responsible for planning, defining, scheduling, documenting, and coordinating reporting and data analytics for the bank. The Head of Data Management & Analytics has oversight of a total of 3 teams: Data warehouse & Business Intelligence team, Central Analytics team & Data Quality control analyst (headcount 12+).

The unit is responsible for the development of statistical methodologies, application tools/programs, and protocols/analyses/reports which support product development, management information & bank’s performance review. The unit has the ultimate accountability for ensuring the volume of work produced meets or exceeds quality level standards of reporting that is required by management and external stakeholder like the BOT. The head manages and direct the daily operations report requirements whilst considering the banks long-term or company initiatives and the impact of those initiatives in reporting.

Responsibilities for the role:

Strategic Planning:

  • Lead strategy around the planning, analysis, and design of MIS & reporting platform to ensure aligned with the overall informatics strategy to build out bank strategic plans
  • Maintains adherence to strategic direction and standards of technology in support of information delivery and analytics.
  • Apply extensive fundamental and specialized knowledge to the development of MIS infrastructure, responding to business requirements, implementing new approaches to automate data processing.
  • Ensures flexibility, scalability and reuse of the IT platform for data processing. Promote best practices and standards in software design and development.
  • Proposes new ideas and recommendation on data management leading to enhanced efficiencies and faster review and analysis of data.
  • Manage and attain customer expectations and ensure delivery fulfill expectations.
  • Ensure to exercise decision-making and independent judgment.

Management Information Reporting & Analytics

  • Provides functional excellence in the areas of statistics, data analysis and data processing for the bank by offering high quality of analysis for all aspect of the business
  • Champion a data-driven, fact based approach to management.
  • Establishment /Implementation of a good business Intelligence tool that can be used to transform raw data into meaningful information. Development of reporting packages both standard as well as support (ADHOC) analytics.
  • Produce meaningful metrics and offer fact based insights to help guide strategies for brand positioning, customer retention, and development, pricing, product innovation, industry competition and cost effective methods of attracting new business.
  • Lead a team of analysts in data exploration and analytics in support of business strategies. Drive best practices around descriptive analytics with team
  • Support business requirement on reporting environment: by defining and implement reporting strategy. Act as link between technical team and business: interpret business requirements, define technical vision and ensure business needs are met.
  • Support the business managers to understand the health of the business, find growth levers, identify marketing challenges and find productive ways to address the opportunity for optimization
  • Drive the performance of current and new product initiatives by leveraging appropriate statistical techniques and infrastructure
  • Assist business with analysis and data mining capabilities by transforming raw data into meaningful management information which assist in solving hard analytical problems
  • Internal development of dashboards for senior management’s use in decision making process. Ensure efficiency in accessing reports through easy accessibility of management reports to all key business users.

Data warehouse & Business Intelligence tool Management:
  • Manage the life cycle of data integration, data transmission, operational analytics into enterprise data environments- Data warehouse by diagraming technical decompositions, describes technical process and data components, and designs exception handling and controls.
  • Leads the strategic technical planning, analysis, and design of the integrated analytical information assets of the Data warehouse.
  • Collaborate with BI analysts, data architects and BI architects during data modeling, data mapping and system specification activities
  • Transforms business-oriented functional specifications into detailed technical specifications. 
  • Create and maintain metadata to ensure consistent metric definitions and nomenclature is used within the EDW/BI environment.
  • Coordinate and engage with business partners and the integration and delivery of the information warehouse environments and associated deliverables through the effective management of the supporting data and operations teams.
  • Partners with IT management and IT architecture, software engineering, and service delivery organizations, as well as the Operations Center in delivery of the warehousing and information environment for, the user applications and tools enabling access to the bank’s information asset, and in support of the hosting and daily operations of these assets
Data Quality Management
  • Establish a clear data quality policy for the bank. Provide high level of data quality awareness across multiple staff profiles within the bank.
  • Research and determine scope and complexity of data quality issue to identify steps to fix issue. Evaluate and identify the data quality gap from people, process and system perspectives.
  • Ensure a consistency review of post load audits to identify, compare, and resolve data quality problems. 
  • Work with Developers & Data Warehouse team to correct data quality errors. Improve data quality, reports validity and consistency.
  • Recommend process improvements to enhance overall data quality.  
  • Ensure adherence to data quality standards. Act as a key link of cross-functional cooperation when it comes to data quality policy implementation.
  • Resolve all internal data exceptions in timely and accurate manner. Filter and “clean” data and review reports for any data quality issues and locate the originating problem area.
  • Analyze, query and manipulate data according to defined business rules and procedures set in the Data Quality Management tool.
Project Management:
  • Responsible for the leadership and technical direction to project managers to ensure consistency and successful delivery of multiple, simultaneous projects within the portfolio.
  • Assist in the definition of project scope and objectives, involving all relevant stakeholders and ensuring technical feasibility. Develop a detailed project plan to monitor and track progress
  • Collaborate with development teams to guide the implementation of project under the unit. Interfaces with business partners and development teams from the inception of the project assisting with finalizing the production support strategy.
  • Manage financial tracking and budgeting, procurement and vendor management related to project management activities for solutions providers, staff augmentation firms, and software providers to ensure compliance with budget and contract spending limitations, federal and Association procurement and ethics requirements, and timely and accurate payments and accruals.
  • Partners with the bank’s business customers and technical partners to understand business needs build relationships and manage business customer satisfaction and leverage technical partner capabilities.
  • Collaborates with Enterprise IT peers to engage a development team that balances internal skills and the required levels of staff augmentation, consulting, and development center resources. Collaborates with business consultants, project teams, and business leaders to ensure business customer needs are met.
  • Manage changes to the project scope, project schedule, and project costs using appropriate verification techniques. Measure project performance using appropriate tools and techniques
People Management:
  • Provide strategic direction to Data Management & Analytics unit and ensure alignment and in support of the bank-wide strategy
  • Hire and continue to build a world class of data science team
  • Ensure the development of a high- performing team through embedding formal Performance appraisal and informal coaching. Manage team on how to conduct meaningful Performance appraisal discussions with their direct reports and ensure that they conduct the process effectively
  • Determine and analyze training and development needs for people. Ensure that identified training is budgeted for and executed
  • Establish and maintain a succession plan for the key roles in the area
  • With the support from the HR Business Partner, interview and recruit new members and provide support to them during the recruitment of their teams on request
  • Ensure that all poor performance is addressed through the NMB Performance guidelines and that continued poor performance is adequately dealt with.
  • Develop appropriate employee opinion survey action items together with the management team of the business unit and ensure that items are executed
  • Motivate employees in the department and ensure that their efforts are recognized
Qualifications and Experience
  • Graduate /Masters in – Business or Accounting and Finance/ Computer Science/Mathematics  OR  Post-graduate – Business or Accounting and Finance/ Computer Science/Mathematics
  • 10+ years of experience in managing business partners and providing management information, descriptive Analytics or related field
  • Strong managerial and interpersonal skills
  • Demonstrate ability to communicate complex issues and concepts in a simple manner. Excellent verbal communication, writing and interpersonal skills.
  • Demonstrate ability and experience to develop and defend technical recommendations and budgetary plans
  • Extensive experience in core Data Management activities (e.g., DM Plans, data edit specifications, understanding of database dictionaries/specs, electronic data transfers, efforts/process in data quality assurance, use of banking coding dictionaries).
  • Knowledge and experience with various databases and key technologies (e.g., Business Intelligence, Data Warehouse)
  • Thorough knowledge of the main features of the collection of data and the relationship of data elements to each other
  • Demonstrate experience and ability to work effectively in a dynamic, collaborative and fast-paced atmosphere
  • Knowledge and experience with data warehouses and analytics and reporting tools. Experience in MI and Business analysis.


Thanks for reading Head of Data Management and Analytics at NMB Bank Plc, May 2018

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