Data Scientist - Global Supply Chain Optimization

Ciena; United Kingdom; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

Ciena is seeking a Data Scientist for Supply Chain Optimisation to tackle global supply chain challenges through advanced analytics. You will design optimization models, apply ML and statistical techniques, and transform large datasets to drive cost efficiency and sustainability across procurement, planning, and logistics.

Role emphasizes production-ready Python solutions, dashboards, and collaboration with diverse teams to deliver scalable analytical outcomes aligned with business priorities.

Qualifications

• Must have 5+ years in data science, analytics, or optimization roles.
• Proficient in Python for analytics and modeling.
• Experience applying ML and statistical modeling in supply chain contexts.
• Experience with optimization libraries (OR-Tools, Pyomo, or Gurobi).
• Proficient in SQL for data manipulation and analysis.

Responsibilities

• Design and implement optimization models for network design, inventory, demand forecasting, and transport.
• Apply analytics to improve cost, service levels, and sustainability.
• Cleanse and transform large datasets to generate insights.
• Develop algorithms using optimization, ML, and statistical methods.
• Build production-ready analytical solutions in Python or similar languages.
• Create dashboards and outputs communicating insights to technical and non-technical stakeholders.
• Collaborate with data scientists, analysts, and architects to ensure scalable solutions.

Skills

Python

SQL

Machine learning

Statistics

Optimization

Data analysis

Education

Data Science degree

Statistics

Mathematics

Operations Research

Computer Science

Tools

OR-Tools

Pyomo

Gurobi

Snowflake

dbt

Dataiku

Alteryx

Job description

Ciena is seeking a Data Scientist for Supply Chain Optimisation to tackle global supply chain challenges through advanced analytics. You will design optimization models, apply ML and statistical techniques, and transform large datasets to drive cost efficiency and sustainability across procurement, planning, and logistics.

Role emphasizes production-ready Python solutions, dashboards, and collaboration with diverse teams to deliver scalable analytical outcomes aligned with business priorities.