Ciena is hiring for a Remote Data Science Intern in US

Position:

Data Scientist Intern
Entry-level opportunity designed for students or recent graduates pursuing relevant technical education

Company:

Ciena
A global leader in networking systems, services, and software with a focus on flexible, people-first work culture

Location:

Remote - United States
Work from anywhere within the US, ensuring accessibility and flexibility

Job type:

Full time
Requires a full-time commitment with flexible scheduling aligned to project and team needs

Job mode:

Internship
Temporary opportunity structured to offer real-world experience and learning

Job requisition id:

R027795

Years of experience:

Not explicitly required
Open to students or fresh graduates with relevant technical skills and academic exposure

Company description:

Ciena is a recognized leader in the networking industry, renowned for its people-first culture and human-centric innovation.
The company is dedicated to building solutions that power the world’s most advanced networks while integrating social, environmental, and community-conscious strategies.
Employees at Ciena thrive in an inclusive environment, where flexibility, autonomy, and personal growth are actively encouraged.
The organization supports work-life integration through remote roles and flexible hours, believing that employee satisfaction leads to higher innovation and performance.
Ciena also emphasizes sustainability, diversity, and ethical practices across its operations, from technological development to workforce engagement.
It combines technical excellence with a deep sense of corporate responsibility, making it a destination employer for mission-driven professionals.
The company's commitment extends beyond technology - it’s about meaningful societal contribution and driving positive global impact.
With strong values and a collaborative culture, Ciena continues to attract top talent passionate about shaping the future of communication networks.

Profile overview:

This Data Scientist Intern role involves hands-on exposure to machine learning, AI, and data engineering tasks.
Interns are expected to research, prototype, and apply Large Language Models (LLMs) to practical use cases that support Ciena’s technology solutions.
The position includes data exploration, predictive modeling, and the development of software tools that automate and optimize analysis workflows.
Interns will participate in cross-functional collaborations, gaining an understanding of how data science aligns with broader business needs.
They will engage in interpreting complex datasets and providing meaningful insights that support product development and innovation.
The role also requires effective communication of technical concepts to both technical and non-technical stakeholders.
Staying current with industry trends and applying the latest advancements in data science and AI will be a core part of the internship.
Ultimately, the role offers a structured learning experience with the opportunity to make real contributions to Ciena’s innovation pipeline.

Qualifications:

Currently pursuing a Bachelor's degree in Computer Science, Data Science, Physics, Statistics, or a related technical field.
Strong foundational knowledge in Python programming, including hands-on familiarity with its packages and frameworks.
Capable of designing, training, and deploying machine learning models in practical environments.
Solid grasp of key computer science principles such as data structures, software design, and data modeling.
Strong analytical thinking and logical reasoning ability to solve complex problems using data.
Must have strong organizational skills and attention to detail, enabling accurate data management and documentation.
Ability to prioritize and manage multiple projects simultaneously in a fast-paced working environment.
Communication skills are essential for translating analytical findings into actionable business strategies.

Additional info:

Familiarity with cloud computing platforms such as AWS, GCP, or Azure is desirable.
Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes adds value.
Working knowledge of Linux environments and scripting in bash is a plus for infrastructure-related tasks.
Exposure to data visualization libraries such as Plotly, Matplotlib, or Grafana is helpful in reporting and dashboards.
Experience with big data and data manipulation tools (e.g., SQL, Pandas, Apache Spark) will be an advantage.
Understanding of modern ML tools such as XGBoost, scikit-learn, TensorFlow, Kedro, or MLflow is preferred.
Familiarity with generative AI frameworks including LangChain, LangGraph, or LangFlow is seen as a bonus.
Prior experience with Agile methodologies, data preprocessing, and professional certifications in machine learning will distinguish candidates.
Knowledge of networking concepts or prior exposure to networking projects is also an added plus.
Compensation includes competitive pay and benefits including health insurance, paid time off, and access to Ciena’s Employee Stock Purchase Program.

Key Responsibilities and Detailed Role Breakdown

Research & Application of LLMs:

Investigate state-of-the-art Large Language Models and explore their use in solving real-world business challenges
Adapt open-source or proprietary AI models for domain-specific problems at Ciena
Experiment with prompts, embeddings, and training methods to enhance model outputs

Data Interpretation & Insight Generation:

Analyze structured and unstructured data to uncover trends, anomalies, and actionable insights
Use advanced statistical techniques to develop data-driven recommendations
Support decision-making through analysis presentations and summary reports

Predictive Modeling & Machine Learning:

Design and deploy ML pipelines from feature engineering to model evaluation
Build supervised and unsupervised learning models to support forecasting and classification tasks
Use tools like scikit-learn, XGBoost, and TensorFlow for experimentation and model development

Automation & Software Engineering:

Create automated scripts and tools that streamline repetitive data tasks
Develop APIs or internal tools for accessing models or data insights within different teams
Support data engineering efforts by contributing to clean, reusable, and scalable codebases

Team Collaboration:

Engage in sprint planning, code reviews, and team retrospectives
Collaborate with data engineers, software developers, and domain experts to meet joint objectives
Participate in brainstorming sessions and architecture discussions to design end-to-end solutions

Communication & Stakeholder Engagement:

Translate complex data processes and outcomes into simple language for broader audiences
Prepare visuals, demos, and write-ups that align technical work with business objectives
Respond to queries and provide updates to both technical mentors and business leads

Keeping Up with Industry Trends:

Regularly follow new developments in AI, ML, and data infrastructure
Contribute ideas for internal improvement based on recent innovations or academic breakthroughs
Document findings from research in formats that support long-term team knowledge sharing

Operational Flexibility and Learning:

Interns will operate in a flexible environment where outcomes matter more than work hours
Encouraged to explore various areas within data science and adjacent technical domains
Receive feedback and mentorship to accelerate learning and professional development

Company Values and Cultural Fit

People-First Culture:

Ciena is deeply committed to creating a supportive, flexible, and inclusive workplace
Values employee growth, learning, and mental well-being over rigid corporate structures
Encourages experimentation, autonomy, and continuous feedback

Equal Opportunity Employer:

Promotes diversity and inclusion at all levels of hiring and employment
Does not discriminate based on gender, race, disability, or veteran status
Will accommodate employees with different needs for accessibility and comfort

Sustainability and Impact:

Invested in environmental stewardship and ethical innovation
Strives to create positive change through sustainability initiatives and social outreach
Encourages employees to align personal values with professional work

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