Data analysis: produce in-depth analysis to identify trends, patterns, and opportunities within the supply chain data, offering valuable insights to drive business impact; Data Integration: Clean, prepare and transform raw data to make it suitable for analysis, ensuring data quality and reliability, working with data engineers; Predictive modeling: Develop advanced predictive models and algorithms to optimize inventory management, demand forecasting, material procurement, KPI optimization; Data visualization: Create clear and insightful data visualizations to communicate findings and support decision-making; Continuous improvement: Stay up to date with the latest data science techniques, tools, and technologies, and propose their application by building business cases
Requirements:
Bachelor’s with 3 years of experience or Master’s with strong academic record in Mathematics, Computer Science, Information Technology, Engineering or related field; Proficiency in programming languages (Python, R, Julia, Scala), ETL (SQL, Informatica, Apache Spark/Databricks) and data platforms (Snowflake, Fabric, Oracle); Experience in supervised and unsupervised machine learning and in using data science libraries (NumPy, Pandas, Scikit-learn, TF, Keras, XGBoost etc); Familiarity with BI and visualization tools (MS Power BI, Matplotlib, Seaborn); Experience using an Agile environment (Jira, Azure DevOps, Kanban…)
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Junior Data Scientist Data analysis: produce in-depth analysis to identify trends, patterns, and opportunities within the supply chain data, offering valuable insights to drive business impact; Data Integration: Clean, prepare and transform raw data to make it suitable for analysis, ensuring data quality and reliability, working with data engineers; Predictive modeling: Develop advanced predictive models and algorithms to optimize inventory management, demand forecasting, material procurement, KPI optimization; Data visualization: Create clear and insightful data visualizations to communicate findings and support decision-making; Continuous improvement: Stay up to date with the latest data science techniques, tools, and technologies, and propose their application by building business cases Bachelor’s with 3 years of experience or Master’s with strong academic record in Mathematics, Computer Science, Information Technology, Engineering or related field; Proficiency in programming languages (Python, R, Julia, Scala), ETL (SQL, Informatica, Apache Spark/Databricks) and data platforms (Snowflake, Fabric, Oracle); Experience in supervised and unsupervised machine learning and in using data science libraries (NumPy, Pandas, Scikit-learn, TF, Keras, XGBoost etc); Familiarity with BI and visualization tools (MS Power BI, Matplotlib, Seaborn); Experience using an Agile environment (Jira, Azure DevOps, Kanban…)
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