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Global Supply Chain Data Scientist

As part of the Global Supply Chain data science team you work on data transparency for Hyva. In our organization lives the paradigm that data is not available and accurate. The data science team is working and proving that this paradigm is not correct.

We mainly develop in the Microsoft environment on premise, Azure and Power Bi at the moment. Where we have BI Analysts in our it team  working on the ETL process that results in a validated global data model and datasets that are sourced directly from our ERP and other key systems. The data science team sets the requirements of Global Supply Chain in the global data model together with the global network leads and Global business process owners but always to support the regions.

As a team you will have a sandbox environment to do rapid prototyping but once validated Specifications are written to be implemented by the BI team in the back-end This enables you and the team to focus on the fun stuff of developing and going very quickly in support of the regions. Where the expectation is to go and learn fast and to surprise the organization with speed and quality. And that data is available… and by making this transparent we drive the accuracy.

MAIN TASKS AND RESPONSIBILITIES

  • Set the requirements of Global Supply Chain for the global data model for the different business processes globally
  • Develop reporting systems for the global manufacturing and business process performance measurement.
  • Direct contact with each region but working on central set priorities together with all roles in global supply chain management
  • Develop power bi dashboards which efficiently support the Weekly, monthly quarterly performance management meetings with each plant, country and region
  • Develop workflow tools with integrated reporting and analysis
  • Lead & own the development and implementation of standard repetitive data handling tools for SI&OP & other workflows (for sales, procurement, demand & supply planning, manufacturing, quality).
  • Monitor the data transparency & integrity, provide information & recommendation to data owners (use analytics to discover data transparency problems).
  • Develop Define data accuracy metrics for different elements within the business master data, transactional data etc.
  • Understand the business processes and data that you are working on, to ensure that what you make is meeting business requirements
  • You possess the ability to speak the language of IT but also from the business process owners to translate the ask from the business into IT Requirements
  • Determine the requirements to improve and implement data models and algorithms to enable automatic readily available KPI reports by end users.
  • Analyze the possibility to address Ad-hoc analytical reports to develop KPI dashboard for them (aim to optimize, combine into regular reports & self-use).
  • Experiment and Implement RPA, Power Apps and Power Automate via fast return on investment use cases where this is suitable and delivering business value as well as drive the development of data workflow and RPA tooling over the axis of cost reduction and efficiency improvements
  • You possess the skills to break the paradigm that data is not available… and are an excellent networker

 

POSITION REQUIREMENTS

Educational Level:

  • Business & IT, Business Information Technology degree, or equivalent
  • Microsoft Certified: Power BI Data Analyst Associate
  • Microsoft Certified: Power Platform Fundamentals

Professional Experience:

  • Minimum 3 years of relevant experience
  • Basic understanding of Supply Chain and manufacturing processes within an ERP system – Infor ERP is a plus.
  • Proficient in Microsoft tools: Microsoft Power Platform (including DAX) and the Microsoft Office Suite
  • Master in SQL or a similar data science language (e.g. R or Python) for prototyping in the sandbox and to ensure we set the proper requirements for the Data warehouse.

Leadership Level: Individual contributor

  • Language: Verbal and Written excellent English

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