Data Scientist - Supply Chain Optimisation
作为高速连接的全球领导者，Ciena 致力于以人为首的方式。我们的团队享有一个专注于优先考虑灵活的工作环境，使个人增长，幸福感和归属成为最重要的文化。我们是一个技术公司，凭借人类精神来领导我们的业务重点，同时与社会，社区和社会的影响产生着意义。数据科学家 供应链优化作为 Ciena 的供应链最佳化团队中的数据科学家，该角色将先进分析应用到对成本，服务性能和可持续性结果直接影响的复杂，全球供应链挑战。该职位为采购，规划，工程，运营和物流功能中的数据驱动决策做出贡献。该角色支持与 Ciena 的运营优先事项一致的可扩展优化解决方案。你将如何产生影响：·设计和实施针对网络设计，库存定位，需求预测和交通效率的优化模型。·应用先进分析技术来提高供应链性能，成本效益，服务水平和可持续发展结果。·分析，清洁和转换大型不完美的数据集以生成可操作见解。· 开发利用优化，机器学习和统计建模技术解决复杂供应链问题的算法。· 使用 Python,R 或类似编程语言实现生产准备分析解决方案。· 建立仪表板和分析输出来向技术和非技术利益相关者传达见解。·与数据科学家，分析师和建筑师合作以确保可扩展和一致的分析解决方案；必须拥有：· 教育：数据科学学位，统计学，数学，运营研究，计算机科学，工程或有关量学科经验：· 在数据科学，分析或优化角色方面有5年以上经验，包括对供应链问题领域的接触。· 应用 Python 或 R 等编程语言用于分析和建模解决方案。·在供应链环境中应用机器学习和统计建模技术。· 使用 OR‐Tools,Pyomo 或 Gurobi 这样的优化库。· SQL 或类似工具用于数据操纵和分析。· 将业务问题的翻译成提供分析方法。
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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.
Data Scientist – Supply Chain Optimisation
As a Data Scientist within Ciena’s Supply Chain Optimisation team, this role applies advanced analytics to complex, global supply chain challenges that directly impact cost, service performance, and sustainability outcomes. The position contributes to data‑driven decision making across procurement, planning, engineering, operations, and logistics functions. This role supports scalable optimization solutions aligned with Ciena’s operational priorities.
How you will make an impact:
- 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.
The must haves:
- Education: Degree in Data Science, Statistics, Mathematics, Operations Research, Computer Science, Engineering, or a related quantitative discipline.
- Experience: 5+ years of experience in data science, analytics, or optimization roles, including exposure to supply chain problem domains.
- 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.
Nice to haves:
- Background working with modern data platforms such as Snowflake and transformation tools such as dbt.
- Exposure to geospatial analytics or network visualization tools.
- Experience supporting global supply chain environments or complex organizational structures.
- Background using Dataiku or Alteryx One.
At Ciena, we are committed to building and fostering an environment in which our employees feel respected, valued, and heard. Ciena values the diversity of its workforce and respects its employees as individuals. We do not tolerate any form of discrimination.
Ciena is an Equal Opportunity Employer, including disability and protected veteran status.
If contacted in relation to a job opportunity, please advise Ciena of any accommodation measures you may require.
Originally posted on Himalayas