Data Scientist – AI Agents, Advanced Analytics

🔥 3 hours ago

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Ciena

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1985

📡 Telecommunications

🔧 Hardware

💰 Series C on 1995-12

Telecommunications • Hardware • Networking

Ciena is a global leader in optical and routing systems, services, and automation software. We build the world’s most adaptive networks to address ever-increasing digital demands for richer, more connected experiences for all users. For three-plus decades, we’ve brought our innate sense of humanity to our relentless pursuit of innovation.

📋 Description

• 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

🎯 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

🏖️ Benefits

• medical, dental, and vision plans • participation in 401(K) (USA) & DCPP (Canada) with company matching • Employee Stock Purchase Program (ESPP) • Employee Assistance Program (EAP) • company-paid holidays • paid sick leave • vacation time