Essential:
- 2+ years of professional experience, including 1+ of DS experience.
- Strong Python coding skills, including using Data Science and Data Engineering libraries.
- Experience with Data Analysis, Data Mining, Statistics or Optimization methods.
- Understanding and experience in applying Data Science/Machine Learning methods to Supply Chain (Manufacturing, Transportation, Warehousing, Inventory or Sustainability)
- Experience in working with Agile project (e.g. Scrum, Kanban), including CRISP-DM delivery framework.
- Experience in working with client-facing role.
- Able to apply independent research, gather information, and give recommendation how to solve problems of diverse scope.
- Great communication skills.
Nice to have:
- Other programming languages knowledge e.g., SQL, R
- Experience working in Spark (PySpark)
- Experience in Python OOP programming in DS context
- Experience in working in other IT roles (Data Engineer, AI Engineer, Business Intelligence-related) is welcomed
- Supply Chain business acumen and background gained in FMCG companies
- Experience working in cloud technologies e.g. MS Azure, AWS
- Strong statistical/mathematical background
- Good understanding and experience in operationalization of models using VMs
- Experience in working in matrix organization
,[The person we are looking for will become part of Data Science & Optimization Team working within DS&AI competency. Person will be responsible for delivering E2E projects, from POCs to scaling up existing solutions, mostly in Supply Chain area for Top500 FMCG companies. , Duties include: , Business understanding, Data understanding/preparation, Modeling, Evaluation and Deployment of solutions – following CRISP-DM methodologies., Experience with business requirements gathering, transforming them into technical plan, data processing, feature engineering, hypothesis testing, transforming findings into tasks, sharing know-how and working on projects as a SME of Supply Chain area, specifically in optimization projects. , Proactive approach for areas where improvement is needed, like suggestions of improving existing pipelines (tests, support, and improvements). , Creating project opportunities in the business (creating use-cases, understanding Customer needs, updates of offerings, success stories updates). , Creation and following of standards to improve competency quality. ] Requirements: Python, SQL, Azure, Data engineering, Machine learning, Kanban, Communication skills, PySpark, Spark, OOP, AI, AWS Additionally: Sport subscription, Training budget, Private healthcare.
Agile feature-engineering statistics Amazon Web Services (AWS) Apache Spark Data Engineering Azure VMS pipeline optimization Communication data-mining Machine Learning OOP PySpark Business Intelligence (BI) Data Analyst mathematics Data Science Python Supply Chain Management standards R modeling SQL forecasting FMCG Scrum Kanban hypothesis-test Initiative