As the global leader in high-speed connectivity, Ciena is committed to a people-first approach. Our teams enjoy a culture focused on prioritizing a flexible work environment that empowers individual growth, well-being, and belonging. We’re a technology company that leads with our humanity—driving our business priorities alongside meaningful social, community, and societal impact.
Ciena is seeking a curious, impact-driven Data Scientist to help shape the next generation of intelligent, data-driven solutions across networking and telecommunications. This role sits at the intersection of advanced analytics, machine learning, and generative artificial intelligence, with a strong emphasis on designing and deploying AI agents powered by Large Language Models (LLMs). The opportunity offers meaningful ownership, technical depth, and the ability to translate emerging AI capabilities into real-world operational and business outcomes.
How you will make an impact :
- Analyze complex, large-scale datasets to uncover patterns, trends, and opportunities that translate into actionable insights and measurable business value
- Design, develop, deploy, and maintain predictive models and machine learning solutions supporting business and operational use cases
- Build AI-powered applications and AI agents leveraging Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), orchestration frameworks, and tool integration
- Research, evaluate, and prototype emerging AI, machine learning, and agentic technologies and assess their applicability within telecom and networking environments
- Develop solutions supporting network operations, automation, incident analysis, anomaly detection, knowledge assistance, customer support, and decision support
- Partner closely with cross-functional stakeholders to define use cases, translate requirements, and deliver scalable, production-ready solutions
- Define and apply evaluation methods and performance metrics for machine learning and LLM-based systems, including quality, reliability, latency, and business impact
The must haves:
- Bachelor’s degree or higher in Computer Science, Data Science, Statistics, Engineering, Physics, or a related quantitative field
- Proven experience in a Data Scientist, Machine Learning Engineer, Applied Scientist, or similar role
- Strong proficiency in Python and hands-on experience with data science and machine learning libraries
- Experience building and deploying machine learning models in production or near-production environments
- Practical experience with Large Language Models (LLMs) and generative AI applications, including prompt engineering, model integration, or retrieval-augmented generation (RAG)
- Solid understanding of AI agent concepts including orchestration, tool use, planning, memory, guardrails, and human-in-th