Head, Data and Artificial Intelligence at Koraplay

About the Role

• The Head of Data and Artificial Intelligence will lead the company’s data strategy and artificial intelligence (AI) initiatives, driving innovation and operational excellence through data-driven decision-making. This role will be responsible for designing scalable data systems, ensuring regulatory compliance, and leveraging AI and machine learning to enhance business operations.
• The ideal candidate is a strategic thinker with a strong technical background in data architecture, AI, and analytics —particularly within the payments industry in emerging markets. They should also possess strong leadership skills to build and develop a high-performing data team.

What You’ll be Doing

Data and AI Strategy and Leadership:

• Define and execute a company-wide data and AI and data strategy that is aligned with business goals.
• Build, mentor, and lead a team of ML engineers, data engineers, data analysts, data scientists, and governance specialists.
• Foster a data-driven and AI-first culture by promoting insights-driven decision-making across teams and 10X growth in our processes and performance.
• Collaborate with executive leadership to align data initiatives with business strategy.

Data Architecture and Engineering:

• Oversee the development of scalable data pipelines, infrastructure, and platforms.
• Ensure seamless integration of data across internal systems, payment networks, and external partners.
• Optimise real-time data processing capabilities for fraud detection, transaction monitoring, and risk management.
• Evaluate and adopt modern data storage, processing, and analytics technologies (e.g., cloud platforms, ETL tools, AI frameworks).

Artificial Intelligence and Machine Learning:

• Identify, adapt, adopt, deploy, or develop AI agents to optimise processes.
• Develop and deploy AI models for fraud detection, customer segmentation, credit risk assessment, and other PSP-specific applications.
• Implement AI-driven personalisation for customer interactions, improving engagement and retention.
• Establish robust MLOps practices to streamline model deployment, monitoring, and lifecycle management.
• Ensure AI models comply with ethical guidelines, minimising bias and ensuring fairness in decision-making.

Regulatory Compliance and Data/AI Governance:

• Implement data governance policies to comply with local and international regulations (e.g., GDPR, NDPR, Kenya Data Protection Act).
• Ensure data privacy, security, and quality across all business units and regions.
• Work with the Legal and Compliance teams to mitigate risks related to data usage.

Business Intelligence and Insights:

• Deliver actionable insights to key stakeholders through dashboards, reports, and advanced analytics.
• Analyse transaction data, payment flows, and customer behaviour to identify trends and business opportunities.
• Improve data accessibility and visualisation across departments to enhance decision-making.

Innovation and R&D:

• Stay updated on advancements in AI, machine learning, and data engineering.
• Explore new technologies to improve operational efficiency and customer experience.
• Lead pilot projects to test and deploy innovative AI-driven solutions.

Change Management & AI Adoption

• Drive organisation-wide adoption of AI-powered decision-making tools.
• Develop training programs and best practices to upskill employees on AI applications.
• Oversee the integration of AI models into existing business processes with minimal disruption.

Budget & Vendor Management:

• Work with the Head of Operations to manage AI and data-related budgets, optimising costs while ensuring high performance.
• Evaluate and recommend third-party vendors, tools, and platforms for AI and data analytics.

Cross-Functional Collaboration:

• Work closely with all teams to embed AI and analytics into all business workflows.
• Partner with the Legal, Compliance, and Risk teams to ensure responsible data usage.
• Act as a thought leader, educating internal stakeholders on AI-driven opportunities.

Requirements

What You’ll Need

You’re qualified if you are/have:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• An MBA or equivalent business experience is a plus.
• 5+ years of experience in data and AI leadership roles, preferably within fintech or payment processing companies.
• Proven expertise in designing and managing large-scale data platforms and AI-driven systems.
• Deep understanding of the payments ecosystem, including fraud prevention and regulatory compliance in Africa.
• Strong track record of driving AI adoption and change management within an organisation.
• Strong programming skills (Python, SQL, R) and experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Proficiency with cloud platforms (AWS, Azure, GCP) and data warehousing tools (Snowflake, BigQuery).
• Experience with data visualisation tools (Tableau, Power BI, Looker).
• Knowledge of data governance and security frameworks.
• Strategic thinker with the ability to communicate complex ideas to non-technical stakeholders.
• Strong leadership and team-building capabilities.
• Exceptional problem-solving skills and attention to detail.
• Ability to drive change and influence cross-functional teams.