Head: Data Science at Capitec Bank

Purpose Statement

• To provide Data Science operational insight and input to Data Services’ strategy to underpin, enable and deliver the organisational strategy.
• To integrate and enable Data Science into Capitec and provide a Guild function to Data Science and Decision Science across Capitec
• To lead and manage the Data Science department, accountable for optimising departmental performance through business planning, budgets, goals and metrics, people, standards, principles and processes.

Experience
Minimum:

Proven experience in:

• 8+ years of experience in managing a team and function to build, develop and deliver Data Science services in an agile and high performing environment, including:
• Business relationship management, especially at a senior/executive level
• Influencing and changing internal culture in respect of Data Science
• Conceptualising and developing innovations and data opportunities and initiatives
• Building machine learning models
• Business analysis and requirements gathering
• Experience in developing and deploying machine learning models into production
• Working in remote environments, e.g. Docker, Linux
• Working in cloud environments, preference for AWS
• At least 5 years’ proven technical experience in;
• Project and task planning and execution at a large scale within a complex and dynamic environment
• Proven experience within one or more of the Data Science and Data Management portfolios 
• Management experience in a team of technical experts 
• Proven track record of delivering on complex Data Science projects
• Proven track record of business relationship management, especially at a senior/executive level

Ideal:

• Experience preferably gained in a financial environment
• Practical experience in applying Agile way of working methodologies within data science
• Proven experience of using influence and relationships to drive and achieve objectives. 
• Experience of successfully leading, planning and managing Data Science initiatives across a large organisation

Qualifications (Minimum)

• Honours Degree in Data Science or Mathematics

Qualifications (Ideal or Preferred)

• Masters Degree in Data Science or Mathematics

Knowledge
Minimum:

• Broad business acumen, in-depth understanding of complex and large organisations; understanding of the full range of business functions and their integration
• Business application of data and analytics at a strategic and tactical level.
• Understanding of organisational cultures and how to impact and influence same.
• How to use consulting and stakeholder relationships, together with change concepts and communication to build an understanding and acceptance of Data Science as a fundamental business tool.
• Understanding of how complex organisations work.
• Leadership or management experience in a team-oriented workplace
• Building and managing effective stakeholder relationships
• Knowledge of data and analytics within the banking or finance industry
• Interlocking and integrating goals, roles, processes, values, communications practices, attitudes and assumptions in relation to organisational culture.
• Underlying theory and application of machine learning models, must be able to understand underlying principles and theory and be able to teach others. 
• Best practices for data science 
• Ethical AI design principles
• Familiar with machine learning applications, solution design and integration to production systems
• Data Science Life Cycle
• Data Product Life Cycle
• Agile principles and methodology
• Understanding of end-to-end D&A environments, including Data Science & Management, Data Warehouse, Business Intelligence and Data Science 
• Data Science practices, business and technology issues related to management of enterprise information assets and approaches related to data protection
• Agile principles and methodology
• Understanding of end-to-end data science and machine learning environments.

Ideal:

• In depth understanding of Machine learning and AI
• Marketing, selling and training Data Science inside an organisation.
• Industry leading data Science and management practices
• Data visualisation of Data Science and management KPIs
• Information systems and information system architecture
• Workflow and process re-engineering
• TOGAF (Data Security and Access Management)
• Knowledge of Cloud and on-premises data solutions (AWS preferred)
• ISF Framework (Data Security and Access Management

Skills

• Leadership Skills
• Strategic Thinking Skills
• Commercial Thinking Skills
• Interpersonal & Relationship management Skills
• Numerical Reasoning skills
• Communications Skills
• Reporting Skills

Competencies

• Deciding and Initiating Action
• Relating and Networking
• Persuading and Influencing
• Analysing
• Creating and Innovating
• Formulating Strategies and Concepts
• Adapting and Responding to Change
• Entrepreneurial and Commercial Thinking

Conditions of Employment

• Clear criminal and credit record
• A valid driver's license and own vehicle is required