Data Scientist – AI Agents & Advanced Analytics

Ciena•Ottawa, ON

1d•$84,200 - $134,600

About The Position

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.

Requirements

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-the-loop approaches
Strong foundation in data structures, software design, system architecture, and analytical problem-solving

Nice To Haves

Experience working with cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform, or Microsoft Azure
Familiarity with Linux-based environments, shell scripting, and containerization technologies such as Docker and Kubernetes
Experience with data and machine learning frameworks including SQL, Pandas, Spark, scikit-learn, XGBoost, TensorFlow, MLflow, Kedro, or similar tools
Exposure to generative AI and LLM ecosystems such as LangChain, LangGraph, Hugging Face, vector databases, or related technologies
Experience with monitoring, evaluation, and observability for machine learning or LLM-based systems
Familiarity with data visualization, reporting tools, Agile development practices, and CI/CD pipelines
Domain knowledge in telecom, networking, OSS/BSS, network assurance, or service operations

Responsibilities

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