View job on Handshake

If you are interested, please apply on our internal workday site:

Telecommunication networks constitute the backbone of modern human interactions. The Custom Solutions Delivery team develops advanced analytics and autonomic solutions to transform customer data into the insights and tools that enable complex network migrations and deliver custom analytical consulting solutions. A key member of the team, the Solutions Analyst is responsible for contributing to the ongoing development of our core innovation capabilities in areas such as network optimisation, network reliability, network transformation, traffic engineer and routing. The Solutions Analyst thinks analytically and creatively, develops heuristics, statistics, and algorithms, and is adept at tailoring outputs and deliverables to suit our client’s needs.

Custom Solutions Delivery Our Mission

The Customs Solution Delivery team is part of the Ciena’s wider advanced services team. Custom Solution Delivery team develops advanced analytics and autonomic solutions to transform customer data into the insights and tools that enable complex network migrations and to deliver custom analytical consulting solutions.​


  • Collaborate in the development of efficient data-collection applications from live networks using REST API, Translation Language 1 (TL1), NETCONF/YANG, etc.
  • Collaborate in the structuring and schema definition of network (big) data into (relational, NoSQL, graph, etc.) databases to represent functional, virtualized networks.
  • Collaborate in the digital transformation of traditional network services by assisting in the analytics and application development that operate on virtualized networks.
  • Collaborate in the mathematical modelling of network optimization problems, including traffic engineering, capacity analysis, routing, resource allocation, load balancing, etc.
  • Research industry and academia to keep up with the latest trends and advances in network and data sciences to support innovative and competitive solution architecture, design, and efficient implementation process and delivery.
  • Advanced data processing and analysis, experience and knowledge are applied with appropriate judgement to deliver reports, outputs and innovative solutions for strategic and project consulting and custom analytical solutions.
  • Defines and builds customer solutions in a rapid development environment, in collaboration with Solutions Consultants and System Architects, to meet the customer requirements and timelines in an efficient manner.
  • Maintains knowledge of available solutions and best practice for consulting processes.

Contribution to Ciena’s success

  • Solutions Analysts are core to sustaining a world-class standard in all aspects of the customer solutions delivery and end-user experience
  • Deep data-analytics know-how and experience, consulting commercial awareness, and strong interpersonal and communications skills to drive consulting engagement success
  • Creating, developing and maintaining solutions, and broadening the range of solutions that consulting can offer ensures a sustainable business revenue model for Ciena

Team(s) with which this role will interact

  • There is a need for client facing meetings – their engineering, IT, planning departments etc., but the main emphasis is close collaboration and coordination with other CSD team members, services sales, the GSS group, as well as the various product groups and BP division when wider contexts are required for any solution
  • Occasionally collaborate with PLM and sales teams to link learnings to pre-sales consulting opportunities
  • Keeping abreast of product developments, particularly APIs and software platforms and frameworks is expected continuously

Experience and personal skills required for the role

  • Minimum: BS (MS preferred) in mathematics, statistics, computer science, physics, engineering or similar.
  • Knowledge in some of the following areas:
  • graph theory
  • math topology
  • linear algebra and/or advanced algebra,
  • theory of algorithms, combinatorics etc.
  • Each of the following is considered a plus:
  • computational/numerical analysis,
  • mathematical optimization
  • linear programming,
  • genetic algorithm,
  • neural networks,
  • machine learning,
  • parallel computing,
  • graph partitioning,
  • clustering.