Data Scientist – Supply Chain Optimisation
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Job Description
Data Scientist utilizing advanced analytics for Supply Chain Optimisation at Ciena. Focused on design, implementation, and improvement of analytics solutions for supply chain challenges.
Responsibilities:
- Design and implement optimization models addressing network design, inventory positioning, demand forecasting, and transportation efficiency
- Apply advanced analytics techniques to improve supply chain performance, cost efficiency, service levels, and sustainability outcomes
- Analyze, cleanse, and transform large, imperfect datasets to generate actionable insights
- Develop algorithms using optimization, machine learning, and statistical modeling techniques to solve complex supply chain problems
- Implement production‑ready analytical solutions using Python, R, or comparable programming languages
- Build dashboards and analytical outputs that communicate insights to technical and non‑technical stakeholders
- Collaborate with data scientists, analysts, and architects to ensure scalable and aligned analytical solutions.
Requirements:
- 5+ years of experience in data science, analytics, or optimization roles
- Degree in Data Science, Statistics, Mathematics, Operations Research, Computer Science, Engineering, or a related quantitative discipline
- Application of programming languages such as Python or R for analytical and modeling solutions
- Application of machine learning and statistical modeling techniques within supply chain contexts
- Utilization of optimization libraries such as OR‑Tools, Pyomo, or Gurobi
- Application of SQL or similar tools for data manipulation and analysis
- Translation of business problems into analytical approaches that deliver actionable outcomes.
Benefits:
- Flexible work environment
- Professional development opportunities
- Recognition initiatives
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