Data Scientist - Supply Chain Optimization
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. As a Data Scientist in the Supply Chain Optimisation team, you will play a key role in applying advanced analytics and data science techniques to solve complex supply chain challenges across procurement, planning, engineering, operations and logistics functions. Reporting to the Head of Supply Chain Optimisation, you will work hands-on with data to develop models and algorithms that optimize supply chain performance, reduce costs, improve service levels, and enhance sustainability. This role is ideal for a mid-career professional with 5+ years of experience in data science or analytics who is eager to deepen their technical expertise while contributing to impactful projects in a global supply chain context. You will have the opportunity to work on a variety of use cases, such as network optimization, inventory management, demand forecasting, and transportation optimization, while collaborating with a cross-functional team of data analysts, architects, and business stakeholders.
Requirements
- Degree in a quantitative field such as Data Science, Statistics, Mathematics, Operations Research, Computer Science, or Engineering.
- 5+ years of hands-on experience in data science, analytics, or optimization roles, ideally with exposure to supply chain problems.
- Proficiency in programming languages such as Python or R.
- Good knowledge of machine learning techniques and their application to supply chain problems
- Experience with optimization libraries (e.g., OR-Tools, Pyomo, Gurobi) and statistical modeling techniques.
- Strong data manipulation skills using SQL or similar tools.
- Experience working with large datasets and applying techniques for data cleaning and transformation.
- Practical experience in at least one of the following areas: Network optimization, Inventory management, Demand forecasting, Transportation optimization
- Proficiency in creating dashboards and visualizations using BI tools (e.g., Power BI, Looker) to communicate insights effectively.
- Ability to translate business problems into analytical approaches and deliver actionable solutions.
- Strong written and verbal communication skills to explain technical concepts clearly to non-technical stakeholders.
Nice To Haves
- Familiarity with modern data platforms (e.g. Snowflake) and transformation tools (e.g. dbt)
- Experience with geospatial analytics or network visualization tools
- Exposure to global supply chain environments or complex organizational structures
- Experience using Dataiku or Alteryx
Responsibilities
- Develop and implement optimization models and algorithms to solve supply chain problems, such as: Network Optimization: Determine the most efficient design for supply chain networks, including warehouse locations, transportation routes, and capacity planning. Inventory Management: Optimize stock levels to balance cost, service levels, and sustainability goals. Demand Forecasting: Build predictive models to improve accuracy in demand planning and reduce supply chain disruptions. Transportation Optimization: Optimize shipping routes and modes to minimize costs and environmental impact.
- Clean, transform, and analyze large datasets to uncover actionable insights, working with imperfect or incomplete data as needed.
- Apply techniques such as linear programming, mixed-integer programming, machine learning, and statistical modeling to tackle supply chain challenges.
- Write production-ready code in Python, R, or similar languages, leveraging libraries such as OR-Tools, Pyomo, or Gurobi for optimization tasks.
- Create dashboards and visualizations using BI tools (e.g., Power BI, Looker) to communicate insights effectively to non-technical stakeholders.
- Partner with other data scientists, analysts, and architects within the Supply Chain Data team to ensure alignment and scalability of solutions.
- Stay up-to-date with the latest developments in data science, optimization techniques, and supply chain technologies, and apply them to improve team capabilities
Benefits
- medical
- dental
- 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
- Paid Family Leave
- other leaves of absence
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
