We are seeking an experienced Head of Data to lead our data strategy, drive data-driven initiatives, and ensure optimal use of data to support business objectives. The role involves defining and implementing data vision, overseeing data teams, collaborating with leadership, ensuring data quality, security, and compliance, and identifying technology partnerships. The ideal candidate has 10+ years of experience in data management, including 5+ years in leadership, expertise in Hadoop, Spark, SQL, NoSQL, cloud platforms, and a strong strategic mindset with excellent communication skills. A degree in Computer Science, Data Science, or related field is required.

Head of Data Strategy at Novancy in Casablanca leads the company's data vision, governance, architecture, and analytics initiatives. The role oversees data engineering, science, and analytics teams, aligning projects with business priorities while ensuring data quality, security, and GDPR compliance. The candidate will identify technology partnerships, manage cloud platforms, and drive AI and MLops practices. With over ten years of experience and a strong background in Hadoop, Spark, SQL, NoSQL, and major cloud providers, the leader will shape data-driven decision making across the organization. This permanent position requires strategic thinking, excellent communication, and a passion for transforming data into actionable insights.

We are seeking an experienced MLOps Engineer – Edge AI Specialist to lead the design and deployment of on‑premise inference infrastructure for industrial vision systems. The role involves architecture of hybrid edge/cloud solutions, model optimization for embedded GPUs, CI/CD pipeline development, fleet management, and compliance with GDPR. The ideal candidate has 3‑5 years of production experience, expertise in TensorRT, ONNX, Kubernetes, and Python, and a strong background in real‑time analytics and GPU performance profiling.

We are seeking an experienced MLOps Engineer – Edge AI Specialist to design and deploy on‑premise inference infrastructure for industrial vision systems. The role involves building hybrid edge/cloud architectures, optimizing deep learning models for embedded GPUs, and maintaining CI/CD pipelines for edge deployment. The ideal candidate will have 3–5 years of experience in MLOps, edge computing, and GPU performance profiling, with strong skills in Python, Docker, Kubernetes, and monitoring tools. This position offers the chance to work in a fast‑moving startup studio focused on scalable AI ventures.