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Graduate - Growing with Data(m/w/x)
Data science project execution and analysis across diverse data types for seed production, including international rotation. Master's/MBA in STEM and good Python/R knowledge required. 30 days vacation, remote work within Germany, overtime compensation with time off.
Requirements
- Master’s or MBA in STEM areas
- Passion for data and value extraction
- Demonstrated leadership potential
- Good knowledge of Python or R
- Knowledge of Viz tools (advantageous)
- Interest in the agricultural industry
- Entry-level or early career status
- Experience in cross-functional projects
- Time spent overseas (advantageous)
- Fluent English language skills
- Availability for full-time work
Tasks
- Plan and execute four data science projects
- Rotate through various business units
- Analyze and manage diverse data types
- Collaborate with different international teams
- Complete a project rotation abroad
- Receive mentorship from the Head of Data Analytics
- Participate in strategic leadership onboarding
- Tour headquarters and R&D centers
- Engage in hands-on agricultural field work
- Attend specialized professional skill trainings
- Share best practices with fellow graduates
- Network with company leaders and alumni
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- R
- PowerBi
- DASH
- Spotfire
- Quik
Benefits
More Vacation Days
- 30 days of paid vacation
- Overtime compensation with time off
Flexible Working
- Flexible working hours
- Remote work within Germany
Bonuses & Incentives
- Holiday and Christmas bonuses
Other Benefits
- Relocation and visa support
Public Transport Subsidies
- Public transport subsidies
Corporate Discounts
- Partner company discounts
Healthcare & Fitness
- Hansefit sports
Team Events
- Cultural and sporting events
Informal Culture
- International work environment
Learning & Development
- Tailored learning and development
- Intensive onboarding program
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Graduate - Growing with Data(m/w/x)
Data science project execution and analysis across diverse data types for seed production, including international rotation. Master's/MBA in STEM and good Python/R knowledge required. 30 days vacation, remote work within Germany, overtime compensation with time off.
Requirements
- Master’s or MBA in STEM areas
- Passion for data and value extraction
- Demonstrated leadership potential
- Good knowledge of Python or R
- Knowledge of Viz tools (advantageous)
- Interest in the agricultural industry
- Entry-level or early career status
- Experience in cross-functional projects
- Time spent overseas (advantageous)
- Fluent English language skills
- Availability for full-time work
Tasks
- Plan and execute four data science projects
- Rotate through various business units
- Analyze and manage diverse data types
- Collaborate with different international teams
- Complete a project rotation abroad
- Receive mentorship from the Head of Data Analytics
- Participate in strategic leadership onboarding
- Tour headquarters and R&D centers
- Engage in hands-on agricultural field work
- Attend specialized professional skill trainings
- Share best practices with fellow graduates
- Network with company leaders and alumni
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- R
- PowerBi
- DASH
- Spotfire
- Quik
Benefits
More Vacation Days
- 30 days of paid vacation
- Overtime compensation with time off
Flexible Working
- Flexible working hours
- Remote work within Germany
Bonuses & Incentives
- Holiday and Christmas bonuses
Other Benefits
- Relocation and visa support
Public Transport Subsidies
- Public transport subsidies
Corporate Discounts
- Partner company discounts
Healthcare & Fitness
- Hansefit sports
Team Events
- Cultural and sporting events
Informal Culture
- International work environment
Learning & Development
- Tailored learning and development
- Intensive onboarding program
About the Company
KWS SAAT
Industry
Agriculture
Description
The company is one of the world’s leading plant breeding companies, focusing on seed production and innovation.
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