Data Scientist, Supply Chain

**About Terex**:
**Position Overview**:
The Data Scientist, Supply Chain will be responsible for the full parts’ lifecycle decision support from analytic question definition, through data engineering, modeling, visualization development, mathematical optimization, operational deployment, and support iterations. This includes working with business stakeholders to gather goals and outline requirements, translate into technical designs, formalize solution algorithms, coordinate with multiple source data owners, and then develop the end user friendly analytics and self-service analytics interfaces.

We are looking for innovators who have ability to drive business results with a passion for discovering solutions hidden in large data sets while working with stakeholders to improve business outcomes. This role will partner with internal supply chain domain experts and external collaboration engagements on advanced analytics and play an important role in the delivery of strategic transformation projects with a focus on analytics and operational research globally.

**Your key responsibilities**:

- Data engineering and integration:

- Active data integration and collection in the data lake from multiple sources and ERP systems around the world.
- Data mapping, standardization, normalization, and curation in forms of materialized views and staging databases.
- Working with relational and hierarchical SQL databases, gathering transactional and BOM information and data required for decision-making.
- Engineering of new features and parts coding.
- Control and update parts’ coding attributes in master data database.
- Mathematical modelling and quantitative decision support:

- Creatively explore, model, simulate and evaluate the material and informational flow from vendors to multi-echelons distribution centers and customer.
- Determine appropriate methods to model parts life cycle, stochastic demand process, maintenance statistics and distribution system dynamics.
- Using and development mathematical optimization methods to solve and formalize material flow paradoxes and conflicting decisions.
- Enabling of discrete event and stochastic simulations methods for future state prediction.
- Visual thinking & storytelling:

- Support developing of automated reporting capability and business performance insights.
- Support the algorithmic reasoning for variance analysis.
- Provide solutions for static visualizations and dynamic dashboards for interpretable data and decision process representation.
- Develop the early warning diagnostic and prescription toolkit.
- Knowledge management and cross-functional collaboration:

- Translate data & analytics into business insights by working with global leaders and regional supply chain teams.
- Taking an active role in preparation and leading of in-house trainings and team upskilling process.
- Improve, standardize, formalize, document, and automate current business processes.
- Enable quantitative decision-making support for cross-functional users.

**Qualifications & Skills**:

- Bachelor or higher degree, preferably in Mathematics, Computer Science, Mechanical Engineering, or relevant quantitative field.
- Advanced knowledge in Math / statistics / heuristic preferably with specialization at least in one area from: predictive analytics / mathematical (linear, convex) optimization / probability and stochastic process.
- Experience with SQL and at least one scripting language (preferable R / Python).
- Exposure to operations research techniques is a plus.
- Strong analytical and problem-solving skills and ability to work under pressure and manage tight timelines.
- Excellent interpersonal skills and a tenacious attitude and ability to work independently and as part of a diverse team.
- Fluent in English, written and spoken, and excellent communication skills (verbal and written) to negotiate and influence internal and external stakeholders.
- Readiness to travel (approximately 20%).