Worldwide Supplies Data Scientist 3D Printing
Reporting into the WW 3D Current Business Director, you will be in charge to develop modeling of the supplies business for 3D, including the agents and the materials (powder) to ensure proper forecasting and planning and identifying trends by predictive analytics.
This is a data scientist position with advanced expertise in DB & modeling, ideally in the supplies 4 box model used at HP.
Your key responsibilities include:
- Supplies modeling infrastructure
- Build a flexible and scalable infrastructure to model the supplies business in terms of top and bottom line, at SKU level by material/agent and subsegments
- Apply statistical modeling, machine learning, and predictive analytics to find patterns and relationships in large volumes of engineering and operative data coming from MJF printers around the world.
- Research and devise innovative statistical models for data analysis focused on supplies demand and 4 box model.
- Enable smarter data processes-and implement analytics for meaningful insights
- Supplies Planning & KPI's
- Run and update supplies KPI on monthly basis
- Drive the analytics to calculate the Supplies LTP, Budget/Quota deployment and quarterly flash
- Develop standard dashboards on supplies
- Support current business management with monthly, quarterly reporting, scorecards and insights for management reviews and clear and compelling communications.
- Supplies Insights
- Identify pattern of supplies behavior by customer, region, segment/sub segment
- Exploratory analysis to discover new opportunities: understanding ecosystems, user behaviors, and long-term trends
- Key Skills:
- Bachelor's degree in statistics, applied mathematics, or related discipline
- Minimum 4-5 years of relevant work experience as a Data scientist / Machine learning from the industry, Strong advantage if background is related to supply forecasting & analytical tools.
- Quick learner with strong statistics background, experience in algorithms programming, data visualization, machine learning and big data.
- Advanced time series, pattern recognition and predictive modeling experience
- Python, R or any other relevant scripting language
- Comfort working in a dynamic, research-oriented group with several concurrent projects
- Exposure to SQL and relational databases
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