Data Science Manager | Gauteng

SUMMARY:
DATA SCIENCE MANAGER | GAUTENG

POSITION INFO:

Job Purpose:

Manage a small team that is responsible for delivering Data Science related objectives in collaboration with the company relevant business units, using mathematical and data related methods (e.g. machine learning, statistical analysis, optimisation, etc.). Responsible for designing, implementing, maintaining, measuring the effectiveness of (e.g. ROI), and optimizing models within the company. These models should drive strategic intent and operational effectiveness.

Responsibilities:

Advanced and Predictive Analytics:

• Employ machine learning techniques and build predictive, descriptive, and behavioral models to help achieve various business performance indicators and to help identify business opportunities, linking insights to actionable recommendations.
• Manage the continuous optimization cycle of these models including implementation, automation, reporting, measuring effectiveness, considering impact on behaviours, considering impact of external factors, redesigning, etc.
• Monitor and quantify the impact of models on the company business, its customers (e.g. customer experience) and other stakeholders.

Data and Analytics Strategy:

• Plan all business and technical aspects of different data and analytics systems and platforms. Understand features and properties, ensure data integrity of new and existing tracking of these systems and platforms.

Information and Business Advice:

• Provide specialist guidance on the interpretation and application of predictive analytics, resolving complex or contentious queries and issues and enabling others to take appropriate actions.
• Present and communicate models, results, etc. up to group exco level.

Stakeholder Engagement:

• Develop stakeholder engagement through identifying stakeholders, finding out their needs/issues/concerns and reacting to these to support the communication of business information and decisions.
• Design and implement Predictive or Renumeration models in consultation with stakeholders (e.g. operational or business units). Build key relationships and collaboration across the business. Assist your Data Science team colleagues across the different areas of Data Science (Data, Analytics, Business Intelligence, Business Analysis, Campaigns) with thoughtful input on methods, logic and reasoning. Equivalently and effectively leverage the assistance of your Data Science colleagues.

Insights and Reporting:

• Contribute to the design and creation of reporting strategies and templates.
• Lead execution of complex reports, identifying and interpreting complex patterns and trends. Present, and communicate high-impact data and analytics insights and recommendations to critical internal and external stakeholders.
• Calculate the ROI of the projects and models and present to key stakeholders.

Data Exploration:

• Perform complex statistical analysis and utilize data mining, modeling, and testing techniques to enable data analysis.
• Understand the different business areas or critical business challenges/ opportunities.

Leadership and Direction:

• Communicate the actions needed to implement the function''s strategy and business plan within the team; explain the relationship to the broader organization''s mission, vision and values; motivate people to commit to these and to doing extraordinary things to achieve local business goals.

Performance Management:

• Develop and propose own performance objectives; take appropriate actions to ensure achievement of agreed objectives, using the organization''s performance management systems to improve personal performance.
• Manage and report on team performance; set appropriate performance objectives for direct reports or project / account team members and hold them accountable for achieving these, taking appropriate corrective action where necessary to ensure the achievement of team / personal objectives.

Data Management:

• Manage key aspects of the data management system with guidance from senior colleagues. This includes being responsible for developing or operating key elements of the system.

Continuous Improvement:

• Review existing operations in own area of work and other business units and implement innovation processes to generate new ideas and ensure the required continuous improvement outcomes are delivered.

Project Management:

• Manage a portfolio of projects while reporting to senior colleagues. Deliver on project outcomes and manage timelines effectively.

Organizational Capability Building:

• Use the organization''s formal development framework to identify the team''s individual development needs. Plan and implement actions, including continuing professional development specified by professional or regulatory institutions, to build their professional capabilities. Provide informal training or coaching to others throughout the organization in own area of expertise to enable others to improve performance and fulfill personal potential.

Personal Capability Building:

• Act as subject matter expert in an area of expertise and take responsibility for personal development in areas including (but not limited to) data, modelling, programming, behavioural analytics, industry and our business through continuing professional development, attending conferences, and reading specialist media.

Technical Competencies:

Machine Learning:

• Use comprehensive knowledge and skills and guide and train others on developing models for planning and monitoring purposes.

Programming:

• Apply comprehensive knowledge / skill, acts and provide guidance and training to others.

• AI, Python, SAS; ABOVE AVERAGE ABILITY TO PROGRAM A COMPUTER..

Numerical Skills:

• Use a comprehensive understanding of numerical concepts to perform mathematical operations such as report analysis while providing guidance and training to others.
• DEEP KNOWLEDGE OF STATISTICS., BASIC BUSINESS AND ACCOUNTING PRINCIPLES.

Data Collection and analysis:

• Guide and train others to analyze data trends for use in reports to help guide decision making.

Review and Reporting:

• Apply comprehensive knowledge and guide and train others to review and create relevant, lucid and effective reports.

Data mining:

• Apply comprehensive knowledge / skill and guide and train others.

Data Management:

• Apply comprehensive knowledge and skills to work and guide and train others to acquire, organize, protect and process data to fulfill business objectives.

Customer and Market Analysis:

• Use comprehensive knowledge to conduct research and analyze data and guide and train others on how to develop a comprehensive understanding of customer and market conditions that enables maximum return on investments.

Business Requirements Analysis:

• Use comprehensive knowledge and skills and guide and train others to analyze the business requirements that solutions must meet.
• Determine acceptance and evaluation criteria.

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