Data Analyst / Supply Chain Management
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Århus C
What you will do
Reporting to the Executive Director, Global Parts Planning, the Data Analyst will play a vital role in analyzing and interpreting data to drive informed decision-making and optimize aftermarket planning on a global scale. Most crucial aspect of this role is to lead the design and development of advanced models for predictive planning to enhance customer satisfaction and optimizing inventory levels. You will work closely with regional planning and service organization to develop key data, analytics, and associated tools/dashboards that provide data-driven insights and solutions.
How you will do it
What we look for
Required
Preferred
#LI-IG1
#LI-Hybrid
Reporting to the Executive Director, Global Parts Planning, the Data Analyst will play a vital role in analyzing and interpreting data to drive informed decision-making and optimize aftermarket planning on a global scale. Most crucial aspect of this role is to lead the design and development of advanced models for predictive planning to enhance customer satisfaction and optimizing inventory levels. You will work closely with regional planning and service organization to develop key data, analytics, and associated tools/dashboards that provide data-driven insights and solutions.
How you will do it
- Utilize machine learning, statistical models and forecasting techniques to develop predictive models based on installed base, and usage.
- Collect, analyze, and interpret large datasets. Identify patterns, correlations, and trends to extract meaningful insight for aftermarket parts planning.
- Analyze demand trends, service levels and inventory to identify opportunities to improve service levels and inventory turns.
- Create and maintain dashboards and regular/ad-hoc reports to showcase planning KPI’s, trends and performance indicators.
- Prepare comprehensive reports and data visualization to effectively communicate key findings, trends, and recommendations.
- Collaborate closely with regional planning teams, service organization and procurement to gather data and insights, align strategies and drive collaborative decision making.
- Support development of S&OP process by developing meaningful visualization and repots.
What we look for
Required
- Bachelor’s degree in Statistics, Data Science, Business Analytics, or Mathematics.
- 5 years of proven experience in data analytics preferably within Supply chain and logistics.
- Proven experience in statistical analysis, data modelling and manipulation and predictive analytics.
- Willingness to travel both domestic and internationally (20-30%) to develop first-hand understanding of sites and the wider organizational challenges.
Preferred
- Advance Degree, MS and/or MBA
- Proficiency in using Python, statistical and visualization tools such as Python, R, Power BI.
- APICS CPIM certification
- Proficiency in using supply planning software and advanced analytics tools.
- Experience in collaborating with multiple sites and business units to achieve business objectives.
- Demonstrated ability to influence senior management, teams and individuals across multiple cultures, disciplines, and geographies.
- Strong verbal and written communication competencies
- Familiarity with the building technologies market.
#LI-IG1
#LI-Hybrid
Information og data
Denne ledige stilling har jobtypen "Øvrige", og befinder sig i kategorien "Øvrige stillinger".
Arbejdsstedet er beliggende i Århus C.
Jobbet er oprettet på vores service den 9.11.2023, men kan have været deaktiveret og genaktiveret igen.
Dagligt opdateret: Dette job opdateres dagligt ud fra jobudbyderens hjemmeside via vores søgemaskineteknologi og er aktivt lige nu.
- Øvrige
- Århus C
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Statistik over udbudte jobs som øvrige i Århus C
Herunder ser du udviklingen i udbudte øvrige i Århus C over tid. Bemærk at jobs der ikke har en bestemt geografi ikke er medtaget i tabellen. I den første kolonne ser du datoen. I den næste kolonne ser du det samlede antal øvrige.
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Statistik over udbudte øvrige i Århus C over tid
Dato | Alle jobs som øvrige |
---|---|
25. december 2024 | 51 |
24. december 2024 | 51 |
23. december 2024 | 51 |
22. december 2024 | 51 |
21. december 2024 | 54 |
20. december 2024 | 53 |
19. december 2024 | 52 |
18. december 2024 | 50 |
17. december 2024 | 47 |
16. december 2024 | 47 |
15. december 2024 | 49 |
14. december 2024 | 48 |
13. december 2024 | 50 |
12. december 2024 | 50 |
11. december 2024 | 49 |
10. december 2024 | 48 |
9. december 2024 | 50 |
8. december 2024 | 55 |
7. december 2024 | 52 |
6. december 2024 | 52 |
5. december 2024 | 50 |
4. december 2024 | 48 |
3. december 2024 | 49 |
2. december 2024 | 41 |
1. december 2024 | 43 |
30. november 2024 | 45 |
29. november 2024 | 44 |
28. november 2024 | 50 |
27. november 2024 | 48 |
26. november 2024 | 48 |
25. november 2024 | 46 |
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