Data Scientist - Service Parts Supply Chain

You will be responsible for working as an Analytics lead for Supply Management, Quality, CO2 and Circular Economy functions. Provide timely and right insights for these functions in addition to responding to adhoc requests eg. EUMDR, operational topics.

To formulate the commercial logistics policy and to create ,lead and coordinate initiatives and activities to achieve optimum integrated management of the goods flow for the markets.

Your role:

• Provide service supply chain(parts) data driven insights to identify and optimize business strategies and enable decision making.
• Drive continuous improvement opportunities to capture value from information on process, performance and advance analytics.
• Ensure daily/weekly/monthly reports are on time and correct.
• Develop dashboards to drive business decisions to ensure SPS KPIs can meet their targets.
• Using new technologies in AI and Simulation to complement descriptive analysis.

You're the right fit if you have:

• Bachelor's/ master's degree in data science, Business Analytics, Supply Chain, Information Systems, Operations Research, or equivalent.
• 8+ years of experience in independently handling Supply Chain Analytices especially parts.

Domain Knowledge & Soft skills:

• Business domain knowledge across multiple disciplines (Supply Chain especially Parts).
• Good communicators to understand and guess what problems stakeholders are trying to solve -> translating high-level into simple and robust solutions is critical.
• Eager to learn new techniques and tools and willingness to do projects in new business areas of Supply Chain especially Parts.
• Ability to visualize and communicate the insights in a meaningful way.

Technical:

• Domain expertise (e.g.  Image recognition, time-series, deep-learning).
• Able to apply statistical techniques to describe data and develop models to make predictions.
• Hands-on experience with Excel (various charts), Power BI visualization Tools.
• Hands-on with experience with complex queries on DBs like Oracle, extracts (eg ETL).
• Should be comfortable with Descriptive, Statistics, Variability, Correlation, Probability, Regression & Normal Distribution.
• Awareness of lean and six-sigma methodologies.
• Computer science skills to write code and be able to work with data engineers to develop software.

How we work together

We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.

Onsite roles require full-time presence in the company’s facilities.

Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.

This is an office-based role.