Job Description

The Gijima Data Strategist is responsible for developing and implementing data strategies that drive business growth, improve decision-making, and enhance operational efficiency. Sound Data strategies are required for the successful implementation of the Enterprise AI Strategy as well as Enterprise Automation. The ideal candidate will have a strong background in data analysis, business acumen, and strategic thinking.POSITION INFO:Formal education * Grade 12

• A degree in Data Science, Computer Science, or related field.

Work experience * Minimum 10 years of experience in the ICT industry.

• Minimum 5 years of experience in data analysis, science or strategy.
• Strong understanding of data modeling, machine learning, and statistics.
• Proficiency in data visualization tools and programming languages.
• Excellent communication and project management skills.
• Business acumen and understanding of industry trends.
• Experience with data governance and quality assurance.
• Strong problem-solving and analytical skills.
• Experience with cloud based data platforms.

Key Skills and Capabilities required Skill requirements consist of the following:

• Strategic thinking and planning.
• Technical Skills in terms of Data Extraction, Data Preparation, Data Visualisation, Data Warehousing and Data Modelling based on complex data sets.
• Mathematical and statistical skills and experience.
• Management Consulting Skills.
• Analytical Skills inclusive of Critical Thinking and Problem Solving.
• High attention to detail.
• Verbal and written Communication Skills.
• Collaboration at all levels in the organisation.
• Project Management Skills.
• Research capability and experience.

Key responsibilities * Data Strategy: Develop and implement comprehensive data strategies aligned with business objectives.

• Projects: Lead data-related projects, ensuring effective data management, analysis, and visualization.
• Collaboration: Collaborate with cross-functional teams to integrate data insights into business decision-making and strategic initiatives.
• Data Management: Develop and manage data management plans, ensuring data quality and integrity.
• Data Architecture: Collaborate with IT teams to design and implement data infrastructure and architecture.
• Data Identification: Identify reliable data sources for both structured and unstructured data, including APIs, Databases, Sensors, etc
• Data Collection: Collect Data from identified sources.
• Data Preparation: Normalise and standardise data formats, schemas, and naming conventions to facilitate data integration. Clean, Transform and Enrich data for including or use by Algorithms.
• Data Ingestion / Integration: Integration of data from different sources into a data lake / data repository.
• Data Analysis and Exploration: Analyse data to identify patterns, gain insights and discover potential problems and/ or opportunities.
• Data Modelling and Evaluation: Use high quality data to train, test and evaluate the AI Models that will solve the identified problems or achieve the required objectives.
• Model Deployment and Monitoring: Deploy the model and implement monitoring to track performance, detect anomalies and mitigate risk in real time.
• Documentation and Knowledge Sharing: Document the Data Architecture and share knowledge with key stakeholders.
• Continuous improvement: Obtain feedback on model performance and outcomes and use information to improve the Data Model.
• Data Quality and Governance: Establish Standards and Policies to ensure data accuracy, completeness, and consistency.
• Trends: Stay up-to-date with industry trends, tools, and methodologies, applying best practices.

Personal attributes * Problem-solving and analytical skills

• Creativity and innovation
• Effective communication
• Collaboration and teamwork
• Strategic thinking and vision
• Integrity
• Dependable

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