Qualification & Experience

Required Knowledge, Skills and Abilities:

• Knowledge and moderate proficiency in R, Python (scikit learn, pandas, numpy, Jupyter etc.) SAS, SQL, MATLAB, C/C++
  
• Understanding of machine learning techniques and algorithms, such as Gradient Boosted Trees, CNN, RNN LSTM, etc.
  
• Experience with data visualization tools ex Tableau, Shiny
  
• Knowledge of the BI/DW lifecycle components including Source Data Analysis, ETL, ODS, Data Marts, and Data Mining.
  
• Expertise with ETL applications like SSIS, Informatica, Data Stage, etc.
  
• Results-oriented leader with a proven track record of leading a data transformation initiative.
  

Mandatory

• Bachelor’s degree and Master's Degree in computer science, Engineering, or related field
  
• Practical experiences in Machine Learning, as well as NLP, Deep Learning (Tensor flow), Statistical Modelling, Quantitative Analysis, Forecasting, Data Visualization
  
• Certifications such as Oracle Certified Master, Certified Data Scientist (The Open Group), Chartered Member and Fellow of the British Computer Society (BCS), and Chartered Member (CPC III) of the Computer Professionals Registration Council of Nigeria (CPN).
  
• 10 - 15 years of demonstrated experience in data management disciplines including data integration, modelling, optimization and/or data quality,
  
• 6 years of progressive leadership experience in leading cross-functional teams and enterprise-wide programs within complex contexts, preferably in the financial services industry
  

• Serve as the corporate data systems Product Manager. Drive the strategy, development and deployment of the Bank’s data systems as well as a roadmap for its future development that aligns with the corporate strategy and business needs.
  
• Continuously assess and recommend enhancements to the Bank’s data architecture and underlying IT infrastructure to ensure data is economically captured, stored, secured, available and usable by appropriate parties throughout the business
  
• Direct prioritization, resourcing, and delivery of data initiatives across businesses and functions including but not limited to: Data Governance, Data Quality, Data Analytics, and Data Architecture.
  
• Define, manage and advance enterprise principles, policies and programs for stewardship, advocacy and custodianship of data and analytics.
  
• Responsible and accountable for the organization and implementation of data governance
  
• Establish Data Management goals, objectives, and operating procedures.
  
• Champion data and analytics value creation and governance as strategic disciplines.
  
• Partner with SBUs to design data analytics projects and develop specific analytical and data science capabilities to achieve organizational goals and operational improvements while enabling and nurturing data-driven decision making.