Reporting to the Group Finance Director, the Head of Data Analysis and Management is responsible for leading KTDA's group data strategy, governance, and analytics functions. The role ensures that data is collected, stored, managed, and analyzed effectively to support evidence-based decision-making, operational efficiency, and strategic growth across KTDA and its subsidiaries.
Key Responsibilities
- Strategy Development: Developing and implementing KTDA’s data management and analytics strategy in alignment with corporate objectives.
- Data Governance: Establishing data governance frameworks, standards, and policies to ensure data quality, accuracy, integrity, and security.
- Compliance: Overseeing compliance with legal, regulatory, and ethical requirements in data management.
- Advanced Analytics: Leading advanced data analytics, modeling, and forecasting to support business planning and operational decisions.
- Business Insights: Providing actionable insights on production, supply chain, market trends, farmer engagement, and financial performance.
- Technology Adoption: Championing the adoption of modern data analytics tools and business intelligence platforms.
- Digital Transformation: Driving digital transformation initiatives, including data automation, big data, and AI-enabled decision-making.
- System Integration: Ensuring integration of data systems across subsidiaries to provide a single source of truth.
- Performance Monitoring: Tracking key performance indicators (KPIs) and providing reports to senior leadership and the Board.
- Strategic Planning: Conducting scenario analysis, trend monitoring, and risk modeling to guide strategic planning.
- Continuous Improvement: Supporting continuous improvement by using data to identify gaps, inefficiencies, and opportunities.
- Team Leadership: Building and leading a high-performing team of data analysts, scientists, and information managers.
- Stakeholder Engagement: Engaging with external stakeholders (regulators, partners, and researchers) to benchmark KTDA against industry best practices.
Qualifications, Skills and Experience
- Education: Bachelor’s Degree in Data Science, Statistics, Computer Science, Economics, Business Analytics, or a related field.
- Advanced Degree: Master’s degree in data science or a related field is an added advantage.
- Certifications: Professional certifications in Data Analytics, Big Data, or BI Tools (e.g., Power BI, Tableau, SQL, Python, R) are an added advantage.
- Experience: Minimum 10 years of progressive experience in data management/analytics, with at least 5 years at a senior management level.
- Track Record: Proven track record in data governance, analytics, and business intelligence in a complex organization.
- Technical Expertise: Strong technical expertise in data analysis, data warehousing, and predictive modeling.
- Knowledge: Excellent understanding of data governance, privacy, and compliance frameworks.
- Analytical Skills: Ability to transform complex datasets into simple, actionable insights.
- Leadership: Strong leadership, project management, and communication skills.
- Attributes: Integrity, analytical thinking, and commitment to KTDA’s farmer-first philosophy.
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