Job Title:                     Chief Data and Analytics Officer (CDAO) - Namibia

Industry:                      Banking

Location:                     Namibia

Salary:                         Competitive Salary Package + Benefits

Job Purpose:

The role of the Chief Data and Analytics Officer is primarily to seek out opportunities to create commercial value from data, through the application of data science, artificial intelligence (AI) and machine learning (ML).  They will also drive the Data Culture in the organisation and promote the embedding of Data-Driven Decision-Making.  They will lead, enhance and mature the Data Science practise by defining the direction, structure, processes and standards for Data Science across the organisation, so that every department and digital capability that relies on data science can benefit from the full potential it, including AI and ML.

The Chief Data and Analytics Officer will also be responsible to drive and oversee the establishment of an enabling Data Governance framework within the organisation covering the elements of strategy, ownership, curatorship, policies, processes, and data quality – with the intention to effectively democratise data for use by the business and power data-driven decision-making.

Key Performance Areas (KPAs)

1. Data Culture

• Responsible for driving the maturity of the data culture in the organisation to better derive commercial value (monetise) data through the use of analytics, AI and ML.
• Acts as a thought leader defining the organisation’s data strategy and data roadmap.

2. Data Science Strategy

• Define the direction, structure, processes and standards for the Data Science practice across the organisation.
• This will include a roadmap for enhancing the maturity of Data Science and the use of advanced analytics, AI and ML for predictive and prescriptive data analytics.
• Ensure the Data Science strategy aligns with business strategy and objectives to ensure commercial viability.

3. Data Governance

• Drive the establishment and embedding of data governance for the organisation, which should cover the areas of:
  • Data strategy
  • Data policies, standards, processes and procedures
  • Data ownership and curatorship
  • Data quality
• Align the data governance programme to the enterprise information strategy.

4. Change Agent

• Educate the organization on the value and benefits of data through the demonstrably and application of analytics, AI and ML.
• Assist the organization become more data-driven in decision making.
• Drive the maturity of the organization in the field of data analytics.
• Manage special projects as assigned to support the implementation of data optimization strategies.

5. Leadership

• Responsible for overseeing the larger Data and Analytics practices in the organisation.
• Provide guidance and leadership to the Data Science, Data Governance and Data Management practises across the enterprise in the form of methods, tools, techniques and resources.
• Strong leader and team-builder and experience in developing, building, and maintaining a business unit.

Core Competences

• Formulating Strategies and Concepts
• Excellent knowledge of data science tools like python, SQL, SAS and AI/ML environments
• Deep understanding of fundamentals of probability and statistics
• Big picture thinking - correctly diagnosing problems and productionising research
• Excellent communication and collaboration skills to partner with business heads and Product Owners

Experience / Knowledge and Skills

• 10-15 years relevant experience in data/analytics
• Experience and expertise in the following: modeling/mathematics, data mining, and data analysis
• Experience and expertise in leading data governance, data quality and data management initiatives
• Experience and expertise in applying and scale-up of real-time analytics methods
• Experience and expertise in the use of applied analytics and predictive/prescriptive analytics, multivariate testing, and optimization algorithms
• Strong fundamental knowledge of probability theory, stochastic systems, Bayesian inference
• Good exposure and use of analytic software tools or languages such as Python, R, SQL, Matlab, SAS, SPSS
• Track record for driving execution of change initiatives in a business
• Leadership and interpersonal skills
• Negotiating and influencing skills

• Excellent data visualisation, presentation and communication/report writing skills

Qualifications

• Master’s degree (PhD preferred) in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field.