Data Science Unit Head JOB

Job Title: Data Science Unit Head

Sector: Strategic Affairs

Department: Data & AI Department

Section: Artificial Intelligence

Direct Manager: Artificial Intelligence Section Head

Role Purpose

To lead the organization’s data science and artificial intelligence initiatives, with a focus on delivering high-impact, scalable AI/ML and Generative AI (GenAI) solutions. The role aims to enhance decision-making, automation, and innovation across business functions through advanced analytics and intelligent systems. 

Key Accountabilities

• Lead the end-to-end design, development, and deployment of AI/ML and GenAI solutions aligned with organizational objectives.


• Translate complex business needs into structured data science problems using statistical modeling, machine learning, and large language model (LLM) approaches.


• Define and execute the AI/ML and GenAI technical roadmap across the organization.

2. Team & Project Management:

• Build and manage a high-performing team of data scientists and GenAI engineers.

• Foster a culture of innovation, continuous learning, and technical excellence.


• Oversee project delivery, ensuring scalability, reliability, and measurable business impact.

3. Hands-on Development & MLOps:

• Actively contributes to solution development, including coding, reviewing, and optimizing ML pipelines, GenAI prompts, and retrieval-augmented generation (RAG) systems.


• Design and maintain robust MLOps and LLMOps workflows for scalable and efficient deployment and monitoring of models.

4. Governance & Compliance:

• Ensure all AI initiatives adhere to data governance, security, privacy, and ethical standards.


• Promote responsible AI practices, including fairness, transparency, and bias mitigation.

5. Technology Evaluation & Integration:

• Evaluate and adopt appropriate technologies (e.g., LLM APIs, open-source models, vector databases) based on performance, cost, and risk.


• Collaborate with IT and business units to ensure smooth integration and adoption of AI solutions.

6. Stakeholder Engagement & Strategy Support:

• Engage with internal stakeholders and external partners to prioritize AI opportunities and define value-driven use cases.


• Support strategic decision-making by delivering insights, dashboards, and presentations to senior leadership.

Qualification (e.g. Academic Qualification, Certifications, Licenses)

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.


• 8–12 years of experience in data science and AI/ML roles, with at least 3–5 years in a technical leadership or team management capacity.


• Proven track record of delivering and scaling machine learning models and GenAI applications in production environments.


• Experience across the full lifecycle of ML and GenAI projects—from data exploration to model deployment and performance monitoring.


• Exposer to transformer models (e.g., GPT, LLaMA, BERT), GenAI toolchains (LangChain, LlamaIndex), and vector stores (FAISS, Pinecone).


• Strong background in programming (Python, SQL) and use of AI/ML libraries (Scikit-learn, PyTorch, TensorFlow).


• Exposure to public sector, culture, tourism, or digital government transformation is a plus.

Critical Skills

• Deep technical expertise in machine learning, deep learning, and Generative AI frameworks.


• Strong capabilities in prompt engineering, LLM integration, and GenAI output evaluation.


• Solid understanding of data science methodologies, model validation techniques, and performance metrics.


• Experience with cloud-based AI platforms (e.g., Azure AI/OpenAI, AWS SageMaker).


• Ability to lead agile teams, manage technical debt, and scale solutions across organizational units.


• Strong stakeholder engagement, communication, and presentation skills.


• Commitment to ethical and responsible AI, including transparency, fairness, and governance compliance.